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Currently used methods for estimation of moisture content in paper pulp are restricted to levels of moisture concentration below 90%. Some of the existing methods require less practical double-sided contact measurements. A few other methods make restrictive assumptions, such as the constituents of the pulp that determine its conductance. This paper presents a technique that uses fringing field interdigital sensors to measure moisture concentration in paper pulp at levels as high as 96%. The method proposed in this paper uses single-sided measurements, offers high sensitivity, and does not require special operating conditions. The accuracy of the proposed method is also demonstrated. The repeatability and reproducibility of the sensor measurements are also shown. [ABSTRACT FROM PUBLISHER]

Partial discharge (PD) characteristics of hexadecane were studied in a needle-plane electrode geometry under AC field with a tungsten needle of 20 μm tip radius. PD experiments were conducted on samples containing known concentrations of oil/paper degradation compounds. Partial discharge inception voltage (PDIV), streamer repetition rates, and phase resolved PD (PRPD) patterns were acquired. Ionization potentials (IP) and electron affinities (EA) of hexadecane and a selection of additives were calculated with density functional theory (DFT) and correlated to PD characteristics. IP did not have a significant effect on the number of streamers initiated as most additives had higher IP relative to hexadecane. The presence of electronegative oxygen changes substantially the PD characteristics and, for most additives, increases the number of positive and negative streamers initiated. The greatest changes in PD characteristics, a reduced number of negative streamers, was observed for compounds with large electron capture cross section, even those with negative EA. [ABSTRACT FROM AUTHOR]

In this paper, the sequence families of which maximum correlation is determined by the Weil bound of exponential sums are revisited. Using the same approach, two new constructions with large family sizes and low maximum correlation are given. The first construction is an analog of one recent result derived from the interleaved structure of Sidel'nikov sequences. For a prime p and an integer M\vert (p-1), the new M-ary sequence families of period p are obtained from irreducible quadratic polynomials and known power residue-based sequence families. The new sequence families increase family sizes of the known power residue-based sequence families, but keep the maximum correlation unchanged. In the second construction, the sequences derived from the Weil representation are generalized, where each new sequence is the elementwise product of a modulated Sidel'nikov sequence and a modulated trace sequence. For positive integers d

In this paper, we establish some criteria to decide when a discrete memoryless channel admits a metric in such a way that the maximum likelihood decoding coincides with the nearest neighbor decoding. In particular, we prove a conjecture presented by M. Firer and J. L. Walker, establishing that every binary asymmetric channel admits a matched metric. [ABSTRACT FROM AUTHOR]

Linear codes achieving or nearly achieving the Singleton bound are interesting in both theory and practice. The objective of this paper is to construct several infinite families of MDS, near MDS and almost MDS codes from some special cyclic subgroups of ${\mathbb {F}}_{q^{2}}^{*}$. To this end, the augmentation and extension techniques are used. The codes in this paper have flexible parameters and their lengths could be large. The minimum linear locality of the codes constructed in this paper is also studied. Some infinite families of optimal linearly locally recoverable codes are obtained. Besides, some codes in this paper are proved to be proper for error detection. [ABSTRACT FROM AUTHOR]

A hybrid communication network with a common analog source signal and independent digital data streams at the transmitters of a multiple access network is considered. The receiver has to estimate the analog signal samples with a given fidelity, and decode the digital streams with a low error probability. The main goal of this paper is to characterize the optimal tradeoff between the mean-squared error distortion in source estimation and the data rates available to each user. To this end, we consider a Gaussian multiple access channel (GMAC) setup with additive state, where the state is nothing but a scaled version of the source process itself. The state process is assumed to be non-causally available to all the transmitting nodes. The problem now becomes that of the joint state estimation and message communication in a GMAC with state. We provide a complete characterization of the optimal distortion-rate tradeoff for an $N$ —sender GMAC. Our results show that, similar to the single-user results, it is optimal to amplify the state using uncoded transmissions, whereas the digital streams are superposed using appropriate Gaussian codebooks in conjunction with dirty paper coding (DPC). Since the variance of the additive state is controlled by a scaling factor in our model, we also recover the results for communicating a common source and independent messages over a GMAC without state as a special case. [ABSTRACT FROM AUTHOR]

The construction of a quasi-cyclic low density parity-check (QC-LDPC) matrix is usually carried out in two steps. In the first step, a prototype matrix is defined according to certain criteria (size, girth, check and variable node degrees, and so on). The second step involves the expansion of the prototype matrix. During this last phase, an integer value is assigned to each non-null position in the prototype matrix corresponding to the right-rotation of the identity matrix. The problem of determining these integer values is complex. The state-of-the-art solutions use either some mathematical constructions to guarantee a given girth of the final QC-LDPC code, or a random search of values until the target girth is satisfied. In this paper, we propose an alternative/complementary method that reduces the search space by defining large equivalence classes of topologically identical matrices through row and column permutations using additive, structural, and multiplicative transformations. Selecting only a single element per equivalence class can reduce the search space by a few orders of magnitude. Then, we use the formalism of constraint programming to list the exhaustive sets of solutions for a given girth and a given expansion factor. An example is presented in all sections of the paper to illustrate the methodology. [ABSTRACT FROM AUTHOR]

Singular divergence-conforming bases have been proposed for the solution of integral equations although they have seen only occasional use in practical applications. The existing singular bases are not hierarchical, which prevents their use in adaptive $ {p}$ -refinement applications. In this paper, a new family of singular hierarchical basis functions is proposed for quadrilateral cells. These functions model the singularities associated with current and charge density at edges and are more convenient for modeling such singularities than triangular bases of the same kind. The basis functions are of the additive kind and combine a hierarchical polynomial representation on quadrilaterals with linearly independent singular terms that incorporate general exponents that may be adjusted for the specific wedge angle of interest. Moreover, the added singular basis functions are computed on the fly. On the basis of various reported numerical results, this paper also illustrates the difficulties, the advantages, the accuracy, and the cost of using such bases in the method of moment solutions of integral equations. [ABSTRACT FROM AUTHOR]

A classical method of constructing a linear code over \mathrm GF(q) with a $t$ -design is to use the incidence matrix of the $t$ -design as a generator matrix over \mathrm GF(q) of the code. This approach has been extensively investigated in the literature. In this paper, a different method of constructing linear codes using specific classes of 2-designs is studied, and linear codes with a few weights are obtained from almost difference sets, difference sets, and a type of 2-designs associated to semibent functions. Two families of the codes obtained in this paper are optimal. The linear codes presented in this paper have applications in secret sharing and authentication schemes, in addition to their applications in consumer electronics, communication and data storage systems. A coding-theory approach to the characterization of highly nonlinear Boolean functions is presented. [ABSTRACT FROM AUTHOR]

Role negotiation is a pivotal step in the role-based collaboration (RBC) process. There are many factors to be considered when decision makers set up criteria to evaluate group performance and agents’ abilities. In this paper, we investigate the applications of three traditional multicriteria decision making methods into role negotiation of RBC, i.e., simple additive weighting, multiplication exponent weighting, and weighted distance. The goal is to acquire ideal and satisfactory methods to set up the evaluation criteria for the role negotiation task. The main contributions of this paper include: 1) a method of generating the matrix of agent qualifications, with a discrete, usually, limited, and finite set of prespecified attributes and values; 2) the upper and lower thresholds of a role’s ability requirements, which are critical parameters for a workable team and its performance; and 3) the potential influences of specialist agents and generalist agents on the group performance. The proposed methods are verified by simulation experiments. The simulation results show that the proposed methods are reasonable, feasible, and practical. [ABSTRACT FROM AUTHOR]

Hardware non-idealities are among the main performance restrictions for upcoming wireless communication systems. Asymmetric hardware distortions (HWD) happen when the impairments of the I/Q branches are correlated or imbalanced, which in turn generate improper additive interference at the receiver side. When the interference is improper, as well as in other interference-limited scenarios, improper Gaussian signaling (IGS) has been shown to provide rate and/or power efficiency benefits. In this paper, we investigate the rate benefits of IGS in a two-user interference channel (IC) with additive asymmetric HWD when interference is treated as noise. We propose two iterative algorithms to optimize the parameters of the improper transmit signals. We first rewrite the rate region as an pseudo-signal-to-interference-plus-noise-ratio (PSINR) region and employ majorization minimization and fractional programming to find a suboptimal solution for the achievable user rates. Then, we propose a simplified algorithm based on a separate optimization of the powers and complementary variances of the users, which exhibits lower computational complexity. We show that IGS can improve the performance of the two-user IC with additive HWD. Our proposed algorithms outperform proper Gaussian signaling and competing IGS algorithms in the literature that do not consider asymmetric HWD. [ABSTRACT FROM AUTHOR]

We consider the problem of recovering a high-dimensional structured signal from independent Gaussian linear measurements each of which is quantized to $b$ bits. The focus is on a specific method of signal recovery that extends a procedure originally proposed by Plan and Vershynin for one-bit quantization to a multi-bit setting. At the heart of this paper is a characterization of the optimal trade-off between the number of measurements m$ and the bit depth per measurement b$ given a total budget of B = m \cdot b -error in estimating the signal. It turns out that the choice b = 1$ is optimal for estimating the unit vector (direction) corresponding to the signal for any level of additive Gaussian noise before quantization as well as for a specific model of adversarial noise, whereas in a noiseless setting the choice b = 2$ is optimal for estimating the direction and the norm (scale) of the signal. Moreover, Lloyd–Max quantization is shown to be an optimal quantization scheme with respect to -estimation error. Our analysis is corroborated by the numerical experiments showing nearly perfect agreement with our theoretical predictions. This paper is complemented by an empirical comparison to alternative methods of signal recovery. The results of that comparison point to a regime change depending on the noise level: in a low-noise setting, the approach under study falls short of more sophisticated competitors while being competitive in moderate- and high-noise settings. [ABSTRACT FROM PUBLISHER]

In this paper, the Two-Way Channel (TWC) with noncausal Channel State Information (CSI) is investigated. For the discrete memoryless channel an achievable rate region is derived. Then by extending the result to the Gaussian TWC with additive interference noise, it is shown that the capacity region of the latter channel is the same as the capacity when there is no interference, i.e., a two-way version of Costa's writing on dirty paper problem is established. [ABSTRACT FROM PUBLISHER]

Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability. In this paper, we first introduce an Additive Angular Margin Loss (ArcFace), which not only has a clear geometric interpretation but also significantly enhances the discriminative power. Since ArcFace is susceptible to the massive label noise, we further propose sub-center ArcFace, in which each class contains $K$ K sub-centers and training samples only need to be close to any of the $K$ K positive sub-centers. Sub-center ArcFace encourages one dominant sub-class that contains the majority of clean faces and non-dominant sub-classes that include hard or noisy faces. Based on this self-propelled isolation, we boost the performance through automatically purifying raw web faces under massive real-world noise. Besides discriminative feature embedding, we also explore the inverse problem, mapping feature vectors to face images. Without training any additional generator or discriminator, the pre-trained ArcFace model can generate identity-preserved face images for both subjects inside and outside the training data only by using the network gradient and Batch Normalization (BN) priors. Extensive experiments demonstrate that ArcFace can enhance the discriminative feature embedding as well as strengthen the generative face synthesis. [ABSTRACT FROM AUTHOR]

Given two discrete random variables $X$ and $Y$ , with probability distributions $p=(p_{1}, \ldots , p_{n})$ and $q=(q_{1}, \ldots , q_{m})$ , respectively, let us denote by ${\mathcal{ C}}(p, q)$ the set of all couplings of $p$ and $q$ , that is, the set of all bivariate probability distributions that have $p$ and $q$ as marginals. In this paper, we study the problem of finding a joint probability distribution in ${\mathcal{ C}}(p, q)$ of minimum entropy (equivalently, a coupling that maximizes the mutual information between $X$ and $Y$), and we discuss several situations where the need for this kind of optimization naturally arises. Since the optimization problem is known to be NP-hard, we give an efficient algorithm to find a joint probability distribution in ${\mathcal{ C}}(p, q)$ with entropy exceeding the minimum possible at most by 1 bit, thus providing an approximation algorithm with an additive gap of at most 1 bit. Leveraging on this algorithm, we extend our result to the problem of finding a minimum-entropy joint distribution of arbitrary $k\geq {2}$ discrete random variables $X_{1}, \ldots , X_{k}$ , consistent with the known $k$ marginal distributions of the individual random variables $X_{1}, \ldots , X_{k}$. In this case, our algorithm has an additive gap of at most $\log k$ from optimum. We also discuss several related applications of our findings and extensions of our results to entropies different from the Shannon entropy. [ABSTRACT FROM AUTHOR]

The hull of a linear code is defined to be the intersection of the code and its dual, and was originally introduced to classify finite projective planes. The hull plays an important role in determining the complexity of algorithms for checking permutation equivalence of two linear codes and computing the automorphism group of a linear code. It has been shown that these algorithms are very effective in general if the size of the hull is small. The objective of this paper is to present some sufficient and necessary conditions that linear codes and cyclic codes have one-dimensional hull. It is shown that there are no such binary or ternary cyclic codes. Based on these characterizations, some constructions of linear codes with one-dimensional hull were given by employing quadratic number fields, partial difference sets, and difference sets. We also construct cyclic codes with one-dimensional hull. Some optimal codes with one-dimensional hull are obtained. [ABSTRACT FROM AUTHOR]

This paper addresses the behavior of a classical multiantenna GLRT test that allows to detect the presence of a known signal corrupted by a multipath propagation channel and by an additive temporally white Gaussian noise with unknown spatial covariance matrix. The paper is focused on the case where the number of sensors M is large, and of the same order of magnitude as the sample size N, a context which is modeled by the large system asymptotic regime M \rightarrow +\infty , N \rightarrow +\infty in such a way that M/N \rightarrow c for c \in (0,+\infty ). The purpose of this paper is to study the behaviour of a GLRT statistics in this regime, and to show that the corresponding theoretical analysis allows to accurately predict the performance of the test when M and N are of the same order of magnitude. [ABSTRACT FROM PUBLISHER]

Manganese-zinc (MnZn) ferrites have important application in convertors and switching mode power supplies. The core losses ($\text{P}_{L}$) of MnZn ferrites have serious influence on the performance of power conversion devices. It is worth emphasizing that reducing the core losses at high frequency is of great significance for the miniaturization and integration of power conversion devices. Here in this paper, MnZn ferrites have been fabricated by the method of solid-state reaction, and the effect of CaCO3 and V2O5 co-additives on the microstructure and magnetic property has been investigated. This paper illustrated the competition mechanism of grain growth, which originated from the hindrance effect of CaCO3 and acceleration effect of V2O5, as well as the effect of CaCO3 and V2O5 on core losses by means of loss separation method. In addition, as for the MnZn ferrite sample with 0.1 wt% CaCO3 and 0.01 wt% V2O5 co-additives, core losses were suppressed to 46 and 664 kW/m3 corresponding to 3 MHz 10 mT and 3 MHz 30 mT at 25 °C, respectively. The state-of-the-art MnZn ferrites with ultralow core losses own potential application for high-frequency power conversion devices. [ABSTRACT FROM AUTHOR]

In this paper, a class of binary three-weight linear codes is constructed. Their dual codes are also studied. The dual codes are either optimal or almost optimal. These codes have applications in authentication codes, secret sharing schemes, and association schemes, in addition to their applications in consumer electronics and communication and data storage systems. [ABSTRACT FROM PUBLISHER]

Face recognition has witnessed significant progress with the advances of deep convolutional neural networks (CNNs), and the central task of which is how to improve the feature discrimination. To this end, several margin-based (e.g., angular, additive and additive angular margins) softmax loss functions have been proposed to increase the feature margin between different classes. However, despite great achievements have been made, they mainly suffer from four issues: 1) They are based on the assumption of well-cleaned training sets, without considering the consequence of noisy labels inherently existing in most of face recognition datasets; 2) They ignore the importance of informative (e.g., semi-hard) features mining for discriminative learning; 3) They encourage the feature margin only from the perspective of ground truth class, without realizing the discriminability from other non-ground truth classes; and 4) They set the feature margin between different classes to be same and fixed, which may not adapt the situation of unbalanced data in different classes very well. To cope with these issues, this paper develops a novel loss function, which explicitly estimates the noisy labels to drop them and adaptively emphasizes the semi-hard feature vectors from the remaining reliable ones to guide the discriminative feature learning. Thus we can address all the above issues and achieve more discriminative features for face recognition. To the best of our knowledge, this is the first attempt to inherit the advantages of feature-based noisy labels detection, feature mining and feature margin into a unified loss function. Extensive experimental results on a variety of face recognition benchmarks have demonstrated the effectiveness of our method over state-of-the-art alternatives. Our source code is available at http://www.cbsr.ia.ac.cn/users/xiaobowang/. [ABSTRACT FROM AUTHOR]

Although significant progress has been achieved recently in automatic learning of steganographic cost, the existing methods designed for spatial images cannot be directly applied to JPEG images which are more common media in daily life. The difficulties of migration are mainly caused by the characteristics of the $8\times 8$ DCT mode structure. To address the issue, in this paper we extend an existing automatic cost learning scheme to JPEG, where the proposed scheme called JEC-RL (JPEG Embedding Cost with Reinforcement Learning) is explicitly designed to tailor the JPEG DCT structure. It works with the embedding action sampling mechanism under reinforcement learning, where a policy network learns the optimal embedding policies via maximizing the rewards provided by an environment network. Following a domain-transition design paradigm, the policy network is composed of three modules, i.e., pixel-level texture complexity evaluation module, DCT feature extraction module, and mode-wise rearrangement module. These modules operate in serial, gradually extracting useful features from a decompressed JPEG image and converting them into embedding policies for DCT elements, while considering JPEG characteristics including inter-block and intra-block correlations simultaneously. The environment network is designed in a gradient-oriented way to provide stable reward values by using a wide architecture equipped with a fixed preprocessing layer with $8\times 8$ DCT basis filters. Extensive experiments and ablation studies demonstrate that the proposed method can achieve good security performance for JPEG images against both advanced feature-based and modern CNN-based steganalyzers. [ABSTRACT FROM AUTHOR]

Single image haze removal, which is to recover the clear version of a hazy image, is a challenging task in computer vision. In this paper, an additive haze model is proposed to approximate the hazy image formation process. In contrast with the traditional optical model, it regards the haze as an additive layer to a clean image. The model thus avoids estimating the medium transmission rate and the global atmospherical light. In addition, based on a critical observation that haze changes gradually and smoothly across the image, a haze smoothness prior is proposed to constrain this model. This prior assumes that the haze layer is much smoother than the clear image. Benefiting from this prior, we can directly separate the clean image from a single hazy image. Experimental results and comparisons with synthetic images and real-world images demonstrate that the proposed method outperforms state-of-the-art single image haze removal algorithms. [ABSTRACT FROM AUTHOR]

The paper addresses an improved inner current reference calculation to be employed in the control of modular multilevel converters operating during either balanced or unbalanced conditions. The suggested reference calculation is derived based on the AC and DC additive and differential voltage components applied to the upper and lower arms of the converter. In addition, the impacts caused not only by the AC network’s impedances but also by the MMC’s arm impedances are also considered during the derivation of the AC additive current reference expressions. Another issue discussed in this article regards that singular voltage conditions, where the positive-sequence component is equal to the negative one, may occur not only in the AC network but also internally (within the converter’s applied voltages). Several different inner current reference calculation methods are compared and their applicability during the former fault conditions is analyzed. The paper presents a detailed formulation of the inner current reference calculation and applies it to different unbalanced AC grid faults where it is shown that the presented approach can be potentially used to maintain the internal energy of the converter balanced during normal and fault conditions. [ABSTRACT FROM AUTHOR]

Recently, subfield codes of geometric codes over large finite fields ${\mathrm {GF}}(q)$ with dimension 3 and 4 were studied and distance-optimal subfield codes over ${\mathrm {GF}}(p)$ were obtained, where $q=p^{m}$. The key idea for obtaining very good subfield codes over small fields is to choose very good linear codes over an extension field with small dimension. This paper first presents a general construction of $[q+1, 2, q]$ MDS codes over ${\mathrm {GF}}(q)$ , and then studies the subfield codes over ${\mathrm {GF}}(p)$ of some of the $[q+1, 2,q]$ MDS codes over ${\mathrm {GF}}(q)$. Two families of dimension-optimal codes over ${\mathrm {GF}}(p)$ are obtained, and several families of nearly optimal codes over ${\mathrm {GF}}(p)$ are produced. Several open problems are also proposed in this paper. [ABSTRACT FROM AUTHOR]

Linear codes generated by component functions of perfect nonlinear (PN for short) and almost perfect nonlinear (APN for short) functions and the first-order Reed-Muller codes have been an object of intensive study in coding theory. The objective of this paper is to investigate some binary shortened codes of two families of linear codes from APN functions and some $p$ -ary shortened codes associated with PN functions. The weight distributions of these shortened codes and the parameters of their duals are determined. The parameters of these binary codes and $p$ -ary codes are flexible. Many of the codes presented in this paper are optimal or almost optimal. The results of this paper show that the shortening technique is very promising for constructing good codes. [ABSTRACT FROM AUTHOR]

In this paper, a family of $[{q}^{2}-1, 4, {q}^{2}-{q}-2]$ cyclic codes over ${\mathbb F}_{{q}}$ meeting the Griesmer bound is presented. Their duals are $[{q}^{2}-1,{q}^{2}-5,4]$ almost MDS codes and are optimal with respect to the sphere-packing bound. The ${q}_{0}$ -ary subfield codes of this family of cyclic codes are also investigated, where ${q}_{0}$ is any prime power such that q is power of ${q}_{0}$. Some of the subfield codes are optimal and some have the best known parameters. It is shown that the subfield codes are equivalent to a family of primitive BCH codes and thus the parameters of the BCH codes are solved. The duals of the subfield codes are also optimal with respect to the sphere-packing bound. A family of $[{q}^{2}, 4, {q}^{2}-{q}-1]$ linear codes over ${\mathbb F}_{{q}}$ meeting the Griesmer bound is presented. Their duals are $[{q}^{2},{q}^{2}-4,4]$ almost MDS codes and are optimal with respect to the sphere-packing bound. The ${q}_{0}$ -ary subfield codes of this family of linear codes are also investigated, where ${q}_{0}$ is any prime power such that q is power of ${q}_{0}$. Five infinite families of 2-designs are also constructed with three families of linear codes of this paper. [ABSTRACT FROM AUTHOR]

In existence of interval-valued parameters and managerial limitations, multicriteria decision-making (MCDM) problems become more complex than their original situation. In such complex cases, the classical MCDM solution methods mainly cannot handle the managerial constraints of the problem and, therefore, become useless. This paper focuses on an MCDM problem such as establishment of the branches of a glass production company in all districts (provinces) of Iran in existence of interval-valued parameters and some managerial limitations like total available budget, number of selected branches for establishment, etc. To overcome the aforementioned difficulties, a novel modified version of the simple additive weighting method, which is of the well-known MCDM approaches of the literature, is formulated as a mixed integer linear formulation. The novelty of this formulation can be summarized by the following points: 1) to cope with the interval values of the criteria; 2) to keep the possibility of selecting a set of best locations among all possible locations; and 3) to handle the managerial limitations of the problem. The proposed formulation is validated by the real data of the case study, and its sensitivity is studied in detail. Finally, the performance of the proposed approach is compared to an alternative proposed solution approach. [ABSTRACT FROM AUTHOR]

In literatures, there are various constructions of frequency hopping sequence (FHS for short) sets with good Hamming correlations. Some papers employed only multiplicative groups of finite fields to construct FHS sets, while other papers implicitly used only additive groups of finite fields for construction of FHS sets. In this paper, we make use of both multiplicative and additive groups of finite fields simultaneously to present a construction of optimal FHS sets. The construction provides a new family of optimal $\left ({{q}^{{m}}-1,\frac {{q}^{{m}-{t}}-1}{{r}},{\it{ rq}}^{{t}};\frac {{q}^{{m}-{t}}-1}{{r}}+1}\right)$ frequency hopping sequence sets archiving the Peng-Fan bound. Thus, some FHS sets constructed in literatures using either multiplicative groups or additive groups of finite fields are included in our family. In addition, some other FHS sets can be obtained via the well-known recursive construction through one-coincidence sequence set. [ABSTRACT FROM AUTHOR]

This paper studies an $n$ -dimensional additive Gaussian noise channel with a peak-power-constrained input. It is well known that, in this case, when $n=1$ the capacity-achieving input distribution is discrete with finitely many mass points, and when $n>1$ the capacity-achieving input distribution is supported on finitely many concentric shells. However, due to the previous proof technique, not even a bound on the exact number of mass points/shells was available. This paper provides an alternative proof of the finiteness of the number mass points/shells of the capacity-achieving input distribution while producing the first firm bounds on the number of mass points and shells, paving an alternative way for approaching many such problems. The first main result of this paper is an order tight implicit bound which shows that the number of mass points in the capacity-achieving input distribution is within a factor of two from the number of zeros of the downward shifted capacity-achieving output probability density function. Next, this implicit bound is utilized to provide a first firm upper on the support size of optimal input distribution, an $O(\mathsf {A}^{2})$ upper bound where $\mathsf {A}$ denotes the constraint on the input amplitude. The second main result of this paper generalizes the first one to the case when $n>1$ , showing that, for each and every dimension $n\ge 1$ , the number of shells that the optimal input distribution contains is $O(\mathsf {A}^{2})$. Finally, the third main result of this paper reconsiders the case $n=1$ with an additional average power constraint, demonstrating a similar $O(\mathsf {A}^{2})$ bound. [ABSTRACT FROM AUTHOR]

This paper shows that for the two-user Gaussian interference channel (G-IC) treating interference as noise without time sharing (TINnoTS) achieves the closure of the capacity region to within either a constant gap, or to within a gap of the order O(\log (\ln (\min ( \mathsf S, \mathsf I))/\gamma )) up to a set of Lebesgue measure \gamma \in (0,1] , where {\mathsf {S}} is the largest signal to noise ratio on the direct links and {\mathsf {I}}$ is the largest interference to noise ratio on the cross links. As a consequence, TINnoTS is optimal from a generalized degrees of freedom (gDoF) perspective for all channel gains except for a subset of zero measure. TINnoTS with Gaussian inputs is known to be optimal within 1/2 bit for a subset of the weak interference regime. Rather surprisingly, this paper shows that TINnoTS is gDoF optimal in all parameter regimes, even in the strong and very strong interference regimes where joint decoding of Gaussian inputs is optimal. For approximate optimality of TINnoTS in all parameter regimes, it is critical to use non-Gaussian inputs. This paper thus proposes to use mixed inputs as channel inputs for the G-IC, where a mixed input is the sum of a discrete and a Gaussian random variable. Interestingly, with reference to the Han–Kobayashi achievable scheme, the discrete part of a mixed input is shown to effectively behave as a common message in the sense that, although treated as noise, its effect on the achievable rate region is as if it were jointly decoded together with the desired messages at a non-intended receiver. The practical implication is that a discrete interfering input is a friend, while an Gaussian interfering input is in general a foe. This paper also discusses other practical implications of the proposed TINnoTS scheme with mixed inputs. Since TINnoTS requires neither explicit joint decoding nor time sharing, the results of this paper are applicable to a variety of oblivious or asynchronous channels, such as the block asynchronous G-IC (which is not an information stable channel) and the G-IC with partial codebook knowledge at one or more receivers. [ABSTRACT FROM AUTHOR]

This paper presents an application of unscented Kalman filters (UKFs) to an automotive electronic throttle device. The motivation of this study is on estimating the position of the throttle device when measurements of the position are inaccessible, e.g., due to failures in the sensor of position. In this case, an external wattmeter is connected in the circuitry to measure the power consumed by the throttle, and this information feeds UKFs to produce the estimation for the position. Experimental data support the findings of this paper. Almost all of the brand-new vehicles based on spark-ignition combustion engines have an electronic throttle valve to control the power produced by the engine. The electronic throttle has a unique sensor for measuring the position of the throttle valve, and this feature can represent a serious problem when the sensor of position fails. As an attempt to prevent the effects of a failure from such a sensor, we present an algorithm (UKF) combined with the use of an additional sensor, i.e., a wattmeter. The wattmeter is detached from the throttle's structure but is arranged to measure the electric power consumed by the throttle. Measurements of the power consumption then feed the UKF. This filter then produces an estimation of the position of the throttle valve. Experimental data illustrate the practical benefits of our approach. [ABSTRACT FROM PUBLISHER]

In this paper, a class of two-weight and three-weight linear codes over \mathrm GF(p) is constructed, and their application in secret sharing is investigated. Some of the linear codes obtained are optimal in the sense that they meet certain bounds on linear codes. These codes have applications also in authentication codes, association schemes, and strongly regular graphs, in addition to their applications in consumer electronics, communication and data storage systems. [ABSTRACT FROM PUBLISHER]

Optical coherence tomography (OCT) has revolutionized diagnosis and prognosis of ophthalmic diseases by visualization and measurement of retinal layers. To speed up the quantitative analysis of disease biomarkers, an increasing number of automatic segmentation algorithms have been proposed to estimate the boundary locations of retinal layers. While the performance of these algorithms has significantly improved in recent years, a critical question to ask is how far we are from a theoretical limit to OCT segmentation performance. In this paper, we present the Cramèr–Rao lower bounds (CRLBs) for the problem of OCT layer segmentation. In deriving the CRLBs, we address the important problem of defining statistical models that best represent the intensity distribution in each layer of the retina. Additionally, we calculate the bounds under an optimal affine bias, reflecting the use of prior knowledge in many segmentation algorithms. Experiments using in vivo images of human retina from a commercial spectral domain OCT system are presented, showing potential for improvement of automated segmentation accuracy. Our general mathematical model can be easily adapted for virtually any OCT system. Furthermore, the statistical models of signal and noise developed in this paper can be utilized for the future improvements of OCT image denoising, reconstruction, and many other applications. [ABSTRACT FROM AUTHOR]

Linear programming approaches have been applied to derive upper bounds on the size of classical and quantum codes. In this paper, we derive similar results for general quantum codes with entanglement assistance by considering a type of split weight enumerator. After deriving the MacWilliams identities for these enumerators, we are able to prove algebraic linear programming bounds, such as the Singleton bound, the Hamming bound, and the first linear programming bound. Our Singleton bound and Hamming bound are more general than the previous bounds for entanglement-assisted quantum stabilizer codes. In addition, we show that the first linear programming bound improves the Hamming bound when the relative distance is sufficiently large. On the other hand, we obtain additional constraints on the size of Pauli subgroups for quantum codes, which allow us to improve the linear programming bounds on the minimum distance of quantum codes of small length. In particular, we show that there is no $[[27, 15, 5]]$ or $[[28, 14, 6]]$ stabilizer code. We also discuss the existence of some entanglement-assisted quantum stabilizer codes with maximal entanglement. As a result, the upper and lower bounds on the minimum distance of maximal-entanglement quantum stabilizer codes with length up to 20 are significantly improved. [ABSTRACT FROM PUBLISHER]

In this paper, we propose CE-BASS, a particle mixture Kalman filter which is robust to both innovative and additive outliers, and able to fully capture multi-modality in the distribution of the hidden state. Furthermore, the particle sampling approach re-samples past states, which enables CE-BASS to handle innovative outliers which are not immediately visible in the observations, such as trend changes. The filter is computationally efficient as we derive new, accurate approximations to the optimal proposal distributions for the particles. The proposed algorithm is shown to compare well with existing approaches and is applied to both machine temperature and server data. [ABSTRACT FROM AUTHOR]

Modern control systems rely heavily on their sensors for reliable operation. Failure of a sensor could destabilize the system, which could have serious consequences to the system's operations. Therefore, there is a need to detect and accommodate such failures, particularly if the system in question is of a safety critical application. In this paper, a sensor failure detection, identification, and accommodation (SFDIA) scheme is presented. This scheme is based on the fully connected cascade (FCC) neural network (NN) architecture. The NN is trained using the neuron by neuron learning algorithm. This NN architecture is chosen because of its efficiency in terms of the number of neurons and the number of inputs required to solve a problem. The SFDIA scheme considers failures in pitch, roll, and yaw rate gyro sensors of an aircraft. A total of 105 experiments were conducted; out of which, only one went undetected. The SFDIA scheme presented here is efficient, compact, and computationally less expensive, in comparison to schemes using, for example, the popular multilayer perceptron NN. These benefits are inherited from the FCC NN architecture. [ABSTRACT FROM PUBLISHER]

Motivated by applications in molecular biology and genotyping, this paper proposes a novel model of group testing for identifying items with real-valued status using nonbinary pooling designs under standard arithmetic observation. The purpose is to learn more information of each item to be tested rather than identify only which ones are defectives as was done in conventional group testing. This paper provides several efficiently decodable nonadaptive strategies for the considered problem. The major tool is a new structure called $q$ -ary additive $(w,d)$ -disjunct matrix, which is related to known structures: 1) the conventional disjunct matrix by Kautz and Singleton 1964 and 2) the SQ-disjunct matrix by Emad and Milenkovic 2012. [ABSTRACT FROM AUTHOR]

Carouseling is an efficient method to mitigate the measurement errors of inertial sensors, particularly microelectromechanical systems (MEMS) gyroscopes. In this paper, the effect of carouseling on the most significant stochastic error processes of an MEMS gyroscope, i.e., additive bias, white noise, $1/f$ noise, and rate random walk (RRW) is investigated. Variance propagation equations for these processes under averaging and carouseling are defined. Furthermore, a novel approach to generating $1/f$ noise is presented. The experimental results show that carouseling reduces the contributions of additive bias, $1/f$ noise, and RRW significantly compared with plain averaging, which can be used to improve the accuracy of dead reckoning systems. [ABSTRACT FROM PUBLISHER]

Recent advances on adaptive steganography imply that the security of steganography can be improved by exploiting the mutual impact of modifications between adjacent cover elements, such as pixels of images, which is called a nonadditive distortion model. In this paper, we propose a framework for nonadditive distortion steganography by defining joint distortion on pixel blocks. To reduce the complexity for minimizing joint distortion, we design a coding method to decompose the joint distortion (abbreviated to DeJoin) into distortion on individual pixels; thus, the message can be efficiently embedded with syndrome-trellis codes. We prove that DeJoin can approach the lower bound of joint distortion. As an example, we define joint distortion according to the principle of synchronizing modification direction and then design steganographic algorithms with DeJoin. The experimental results show that the proposed method outperforms previous nonadditive distortion steganography when resisting the state-of-the-art steganalysis. [ABSTRACT FROM PUBLISHER]

Multiple-input–multiple-output (MIMO) technology can efficiently use the spectrum to increase the communication throughput. Designing low-complexity detection algorithms with high performance for the MIMO system has been an important issue. In this paper, we propose efficient detection algorithms for MIMO systems based on differential metrics. We first define differential metrics and give their recursive calculation of different orders. Based on differential metrics, we give the principle of gradient search. We then propose a gradient search algorithm (GSA) that can provide a tradeoff between performance and complexity. The GSA applies the indicative functions such that we can determine in advance some maximum-likelihood (ML) bits of the initial sequence and reduce the searching range. The GSA also uses a stop condition with which we can stop the search if the proper condition is satisfied. The GSA does not need QR decomposition (QRD) or matrix inversion. The multiplicative operations are only necessary before the searching process, during which only the additive operations are needed. For large-scaled MIMO systems, we also give a simple searching algorithm based on differential metrics. Finally, we propose a fixed-complexity gradient algorithm (FCGA), which has a fixed number of operations during the searching process and is appropriate for pipelined hardware implementation. The simulation results validate the efficiency of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

The brushless doubly fed machine (BDFM), which eliminates slip rings and brushes, shows great potential in application fields where reliability is a prime concern. This paper presents the generalized design methodology of the novel three-phase Y-connected wound rotor for both additive modulation BDFM and differential modulation BDFM with specific schemes. First, the above two types of BDFMs are explicated by magnetic field modulations of two main magnetic fields. Then, design principles are illustrated to further improve the conductor utilization ratio of the rotor winding (RW) and reduce harmonic contents of the magnetomotive force (MMF) with a three-phase AC winding. Design examples and specific procedures of the proposed novel three-phase Y-connected wound rotor are also presented for both additive and differential modulation BDFMs, respectively. Finally, finite element models of two types of the BDFM are established and a differential modulation prototype is manufactured. Proposed design schemes are verified by comparative simulation and experimental results at different speeds and load conditions. [ABSTRACT FROM AUTHOR]

This paper considers Gaussian half-duplex diamond $n$ -relay networks, where a source communicates with a destination by hopping information through one layer of $n$ non-communicating relays that operate in half-duplex. The main focus consists of investigating the following question: What is the contribution of a single relay on the approximate capacity of the entire network? In particular, approximate capacity refers to a quantity that approximates the Shannon capacity within an additive gap which only depends on $n$ , and is independent of the channel parameters. This paper answers the above question by providing a fundamental bound on the ratio between the approximate capacity of the highest-performing single relay and the approximate capacity of the entire network, for any number $n$. Surprisingly, it is shown that such a ratio guarantee is $f = 1/(2+2\cos (2\pi /(n+2)))$ , that is a sinusoidal function of $n$ , which decreases as $n$ increases. It is also shown that the aforementioned ratio guarantee is tight, i.e., there exist Gaussian half-duplex diamond $n$ -relay networks, where the highest-performing relay has an approximate capacity equal to an $f$ fraction of the approximate capacity of the entire network. [ABSTRACT FROM AUTHOR]

Recent research has revealed that the output of deep neural networks (DNNs) can be easily altered by adding relatively small perturbations to the input vector. In this paper, we analyze an attack in an extremely limited scenario where only one pixel can be modified. For that we propose a novel method for generating one-pixel adversarial perturbations based on differential evolution (DE). It requires less adversarial information (a black-box attack) and can fool more types of networks due to the inherent features of DE. The results show that 67.97% of the natural images in Kaggle CIFAR-10 test dataset and 16.04% of the ImageNet (ILSVRC 2012) test images can be perturbed to at least one target class by modifying just one pixel with 74.03% and 22.91% confidence on average. We also show the same vulnerability on the original CIFAR-10 dataset. Thus, the proposed attack explores a different take on adversarial machine learning in an extreme limited scenario, showing that current DNNs are also vulnerable to such low dimension attacks. Besides, we also illustrate an important application of DE (or broadly speaking, evolutionary computation) in the domain of adversarial machine learning: creating tools that can effectively generate low-cost adversarial attacks against neural networks for evaluating robustness. [ABSTRACT FROM AUTHOR]

BCH codes are an important class of cyclic codes which have applications in satellite communications, DVDs, disk drives, and two-dimensional bar codes. Although BCH codes have been widely studied, their parameters are known for only a few special classes. Recently, Ding et al. made some new progress in BCH codes. However, we still have very limited knowledge on the dimension of BCH codes, not to mention the weight distribution of BCH codes. In this paper, we generalize the results on BCH codes from several previous papers. 1) The dimension of narrow-sense BCH codes of length $((q^{m}-1)/{\lambda })$ with designed distance $2\leq \delta \leq (({q^{\lceil (m+1)/2 \rceil }-1})/(\lambda)+1)$ is settled, where $\lambda $ is any factor of $(q-1)$. 2) The weight distributions of two classes of narrow-sense BCH codes of length $(({q^{m}-1})/2)$ with designed distance $\delta =(({(q-1)q^{m-1}-q^{\lfloor (m-1)/2\rfloor }-1})/2)$ and $\delta =(({(q-1)q^{m-1}-q^{\lfloor (m+1)/2\rfloor }-1})/2)$ are determined. 3) The weight distribution of a class of BCH codes of length $((q^{m}-1)/({q-1}))$ is determined. In particular, a subclass of this class of BCH codes is optimal with respect to the Griesmer bound. Some optimal linear codes obtained from this class of BCH codes are characterized. [ABSTRACT FROM AUTHOR]

The additive kernel least squares support vector machine (AK-LS-SVM) has been well used in classification tasks due to its inherent advantages. For example, additive kernels work extremely well for some specific tasks, such as computer vision classification, medical research, and some specialized scenarios. Moreover, the analytical solution using AK-LS-SVM can formulate leave-one-out cross-validation error estimates in a closed form for parameter tuning, which drastically reduces the computational cost and guarantee the generalization performance especially on small and medium datasets. However, AK-LS-SVM still faces two main challenges: 1) improving the classification performance of AK-LS-SVM and 2) saving time when performing a grid search for model selection. Inspired by the stacked generalization principle and the transfer learning mechanism, a layer-by-layer combination of AK-LS-SVM classifiers embedded with transfer learning is proposed in this paper. This new classifier is called deep transfer additive kernel least square support vector machine (DTA-LS-SVM) which overcomes these two challenges. Also, considering that imbalanced datasets are involved in many real-world scenarios, especially for medical data analysis, the deep-transfer element is extended to compensate for this imbalance, thus leading to the development of another new classifier iDTA-LS-SVM. In the hierarchical structure of both DTA-LS-SVM and iDTA-LS-SVM, each layer has an AK-LS-SVM and the predictions from the previous layer act as an additional input feature for the current layer. Importantly, transfer learning is also embedded to guarantee generalization consistency between the adjacent layers. Moreover, both iDTA-LS-SVM and DTA-LS-SVM can ensure the minimal leave-one-out error by using the proposed fast leave-one-out cross validation strategy on the training set in each layer. We compared the proposed classifiers DTA-LS-SVM and iDTA-LS-SVM with the traditional LS-SVM and SVM using additive kernels on seven public UCI datasets and one real world dataset. The experimental results show that both DTA-LS-SVM and iDTA-LS-SVM exhibit better generalization performance and faster learning speed. [ABSTRACT FROM AUTHOR]

Discontinuous Galerkin time-domain (DGTD) methods using explicit time integration schemes often suffer from unreasonably small time-step size when applied to simulations involving electrically small structures. In this paper, an exponential time integration (ETI) scheme based on Krylov subspace is proposed for DGTD. The proposed scheme is unconditionally stable and exhibits good accuracy for large time-step sizes. When compared with classic ETI schemes, in the proposed scheme, the dense matrix exponentials are absorbed in matrix–vector products, hence the prohibitive memory costs are avoided. Moreover, a preconditioner combining the shift-and-invert technique and restricted additive Schwarz method is also developed to accelerate the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the additivity phenomenon in the quantum dynamic capacity region of a quantum channel for trading the resources of classical communication, quantum communication, and entanglement. Understanding such an additivity property is important if we want to optimally use a quantum channel for general communication purposes. However, in a lot of cases, the channel one will be using only has an additive single or double resource capacity region, and it is largely unknown if this could lead to a strictly superadditive double or triple resource capacity region, respectively. For example, if a channel has additive classical and quantum capacities, can the classical-quantum capacity region be strictly superadditive? In this paper, we answer such questions affirmatively. We give proof-of-principle requirements for these channels to exist. In most cases, we can provide an explicit construction of these quantum channels. The existence of these superadditive phenomena is surprising in contrast to the result that the additivity of both classical-entanglement and classical-quantum capacity regions imply the additivity of the triple resource capacity region for a given channel. [ABSTRACT FROM AUTHOR]

In this paper, two different Gray-like maps from $Z_{p}^\alpha \times Z_{p^{k}}^\beta $ , where $p$ is prime, to $Z_{p}^{n}$ , $n={\alpha +\beta p^{k-1}}$ , denoted by $\varphi $ and $\Phi $ , respectively, are presented. We have determined the connection between the weight enumerators among the image codes under these two mappings. We show that if $C$ is a $Z_{p} Z_{p^{k}}$ -additive code, and $C^\bot $ is its dual, then the weight enumerators of the image $p$ -ary codes $\varphi (C)$ and $\Phi (C^\bot)$ are formally dual. This is a partial generalization of [D. S. Krotov, On $Z_{2^{k}}$ -dual binary codes, IEEE Transactions Information Theory 53 (2007), 1532–1537], and the result is generalized to odd characteristic $p$ and mixed alphabet. In addition, a construction of 1-perfect additive codes in the mixed $Z_{p} Z_{p^{2}}\ldots Z_{p^{k}}$ alphabet is given. [ABSTRACT FROM AUTHOR]