Search

A delay of less than one millisecond is required by low-latency 5G wireless communication systems for supporting the “tactile” Internet. Hence, conventional initial synchronisation cannot be readily employed because of its potentially excessive delay. In this paper, an extrinsic information transfer (EXIT) chart assisted approach is used for the convergence analysis of $m$-sequences using recursive soft sequence estimation (RSSE) in the context of Nakagami-m fading channels. Explicitly, the novelty of our work is based on employing a new type of EXIT charts operating without using interleavers. This is a challenge, because the original EXIT charts rely on the employment of long, high-delay interleavers for ensuring that the inputs to the decoders become uncorrelated. We then evaluate the performance of various classes of $m$-sequences with the aid of the proposed EXIT charts and demonstrate that the $m$-sequences generated by the lower order polynomials maximize the mutual information more promptly with the aid of our RSSE scheme than those that belong to a higher order polynomial. [ABSTRACT FROM PUBLISHER]

Contribution: Findings are provided from an initial survey to evaluate the magnitude of the recursion problem from the student point of view.

Background: A major difficulty that programming students must overcome—the learning of recursion—has been addressed by many authors, using various approaches, but none have considered how students perceive this issue.

Research Questions: 1) How can an instrument be developed to characterize the main difficulties students encounter, from their subjective perspective, when learning recursion? and 2) How can the quality of the developed instrument be determined?

Methodology: 1) A development process was followed to create the instrument. This process included justification of the content, and a quality analysis of the instrument in terms of validity and reliability and 2) the study was on a limited number of students, so should be regarded as preliminary with respect to validity and reliability of results.

Findings: 1) An initial survey indicates the magnitude of the recursion problem from the students’ point of view; 2) students’ perception is that neither motivation, nor their previous knowledge of theoretical concepts on recursion, are factors that affect their learning of the recursion process; and 3) for further statistical analysis, data from a simplified survey proved more valid and more reliable than that from the original survey, for the study sample examined. [ABSTRACT FROM AUTHOR]

In this paper, we address the problems of enumerating siphons and minimal siphons in ordinary Petri nets (PNs) by resorting to the semi-tensor product (STP) of matrices. First, a matrix equation, called the siphon equation (SE), is established by using STP. Second, an algorithm is proposed to calculate all siphons in ordinary PNs. An example is presented to illustrate the theoretical results and show that the proposed method is more effective than other existing methods in calculating all siphons of PNs. Third, an efficient recursion algorithm is also proposed, which can be applied to computing all minimal siphons for any ordinary PNs. Last, some results on the computational complexity of the proposed algorithms, in this paper, are provided, as well as experimental results. [ABSTRACT FROM PUBLISHER]

Recursion is one of the most difficult programming topics for students. In this paper, an instructional method is proposed to enhance students' understanding of recursion tracing. The proposal is based on the use of rules to translate linear recursion algorithms into equivalent, iterative ones. The paper has two main contributions: the instructional method itself, and its evaluation, which is based on previous works of other authors on mental models of recursion. As a result, an enhancement was measured in the viability of mental models exhibited by students (both for linear and multiple recursion), but no significant improvement was detected in their skills for designing recursive algorithms. Evidence was also obtained of the fact that many students with (relatively) viable mental models for linear recursion have unviable mental models for multiple recursion. Finally, it was noticed that many students adopt inaccurate mental models if those models are adequate to handle the given algorithm. [ABSTRACT FROM PUBLISHER]

Low-density parity-check (LDPC) convolutional codes (or spatially coupled codes) were recently shown to approach capacity on the binary erasure channel (BEC) and binary-input memoryless symmetric channels. The mechanism behind this spectacular performance is now called threshold saturation via spatial coupling. This new phenomenon is characterized by the belief-propagation threshold of the spatially coupled ensemble increasing to an intrinsic noise threshold defined by the uncoupled system. In this paper, we present a simple proof of threshold saturation that applies to a wide class of coupled scalar recursions. Our approach is based on constructing potential functions for both the coupled and uncoupled recursions. Our results actually show that the fixed point of the coupled recursion is essentially determined by the minimum of the uncoupled potential function and we refer to this phenomenon as Maxwell saturation. A variety of examples are considered including the density-evolution equations for: irregular LDPC codes on the BEC, irregular low-density generator-matrix codes on the BEC, a class of generalized LDPC codes with BCH component codes, the joint iterative decoding of LDPC codes on intersymbol-interference channels with erasure noise, and the compressed sensing of random vectors with independent identically distributed components. [ABSTRACT FROM PUBLISHER]

This paper introduces a generalization of the multiple-hypothesis tracking (MHT) formalism for multitarget tracking. To our knowledge, MHT treatments in the literature do not consider undetected target birth events. Their inclusion leads to an interesting extension to the MHT recursion and necessitates aggregation over indistinguishable global hypotheses. We show that the MHT recursion factors, enabling track-oriented MHT (TO-MHT), albeit with clusters of indistinguishable undetected births. The treatment requires a distinction between those targets that are eventually detected (we call these unnoticed targets) and those that are never detected (we call these ghost targets). While the formulation appears more complex, there is structure to the solution that can be exploited, resulting in the same number of relevant track hypotheses for detected targets as in the classical TO-MHT solution. In the time-invariant case, the solution simplifies further because we need not consider unnoticed targets and there is a fixed structure to the ghost target solution. [ABSTRACT FROM AUTHOR]

Energy harvesting is often used for green communications. The problem of power allocation is then to maximize the throughput, taking into account the fact that channel conditions and energy sources are time varying. In particular, for the constraints of the target problem, besides the allocated power values being nonnegative, the successively harvested energy sum leads to the triangle coefficient matrix of the power sum constraints. In this paper, we propose a geometric waterfilling (GWF) algorithm in place of the conventional waterfilling (CWF) algorithm for power allocation with a sum power constraint. We then recursively apply the GWF as a functional block to sequentially solve the power allocation problem for energy harvesting transmission in a fading channel. This algorithm is referred to as RGWF. The proposed RGWF is further extended to solving the minimization of the transmission completion time (referred to as RGWFn) by inserting a condition to check if the preset information transmission data bits are achieved. Since RGWF is defined by recursion and along natural progress of time, we can compute a family of solutions for subprocesses from epoch 1 to epoch k, for k = \1, \ldots, K, where K is the index of the final epoch for the entire process. Thus, RGWF can be utilized for efficiently carrying out the computation of RGWFn. RGWF and RGWFn belong to dynamical recursive algorithms. Compared with the existing results in the open literature, the proposed algorithms have distinguished features: 1) They provide the exact optimal solutions via efficient finite computation under the recursive category, and 2) the optimality of the proposed algorithms is strictly proven. Numerical examples are provided to illustrate the procedures to obtain the optimal power allocation by using the proposed algorithms. [ABSTRACT FROM PUBLISHER]

Real number block codes derived from the discrete Fourier transform (DFT) are corrected by coupling a very modified Berlekamp-Massey (BM) algorithm with a syndrome extension process. The modified BM algorithm determines recursively the locations of any large errors whose number is within the capability of the DFT code. It evolves a connection polynomial which is changed when a discrepancy is above a threshold which is adjusted during each iteration. The large error locations are repositioned to exact location indices to combat low-level noise effects. The syndromes are extended using the refined connection polynomial taps. Alternately, enhanced extension recursions based on Kalman syndrome extensions are developed and simulated. [ABSTRACT FROM AUTHOR]

We consider an age replacement policy (ARP) for a system which consists of several multi-state elements. These elements can be in different states with performance levels ranging from perfectly functioning (the highest state) to total failure (the zero state). The multi-state system (MSS) is considered to be in a failure or unacceptable state if its performance level, determined by the multiple elements and the configuration, falls below the user demand level, and is considered as in a working or acceptable state if its performance level is greater than or equal to the user demand level. Under an ARP, a multi-state system is replaced at a failure, or at age T, whichever comes first. The deterioration of the multi-state element is assumed to follow the non-homogenous continuous-time Markov chain (NHCTMC). We use the recursion to solve the Chapman-Kolmogorov's (C-K) forward equation to obtain the time-dependent state probabilities of each element of the system. Then we compute the state probabilities of the entire system by using the Lz-transform method. Finally, we derive the expected cost and profit functions, and determine the cost minimization or profit maximization ARPs. The multi-state model under the ARP is a generalization of the classic two-state maintenance model, and can be applied to analyze more complex aging systems. Numerical examples are presented to demonstrate our results. [ABSTRACT FROM PUBLISHER]

A new exact solution to the problem of scattering of electromagnetic waves from multilayer elliptic cylinders moving in the axial direction is proposed. The homogeneous media of the different layers are assumed to be linear and isotropic in their rest frames. All media that are not at rest with respect to the host medium are, moreover, supposed to have an electric conductivity equal to zero (in their rest frames). Starting from the fact that a moving medium can be treated as a stationary bianisotropic one, we deduce the series expansions in terms of Mathieu functions for the electromagnetic fields in the different layers. Then, an efficient recursive procedure for the computation of the solutions is developed. Some numerical results show the reliability of the solution and the efficiency of the recursive procedure proposed. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of the simultaneous estimation of frequency and power components is investigated. It is solved through a new recursive estimator capable of estimating the unknown model parameters during severe dynamic changes in the system. By this, a simple nonlinear parameter model for the instantaneous power, taking into account the fundamental components of voltage and current, is used as a starting point for the power components and frequency estimation. In the model, the system frequency is considered as an unknown model parameter, and it is simultaneously estimated with other unknown parameters. This resulted in an efficient numerical algorithm for the measurement of power components, which is not sensitive to variations of the system frequency. This is an important achievement, which improves the accuracy of the method during network transients. The new estimator has been improved by the strategy for tuning its forgetting factor according to the system dynamics, and it is tested through computer simulations and by using data records obtained under laboratory conditions. The algorithm was developed for a single-phase system, and the approach might be easily extended to multiphase systems. [ABSTRACT FROM AUTHOR]

In this paper, a framework for obtaining the higher order derivative of digital signals with an improved signal-to-quantization-noise ratio (SQNR) is developed. The framework consists of an oversampling analog-to-digital conversion unit with a dithering process and a higher order finite-impulse response (FIR) digital differentiator followed by a decimator. A simple and effective recursion is derived for designing the higher order FIR digital differentiator. In addition, the SQNR is analyzed. Computer simulations validate the proposed framework, the differentiator design method, and the results of the improved SQNR. [ABSTRACT FROM AUTHOR]

This paper presents an alternative technique for the adaptive control of power electronic converter circuits. Specific attention is given to the adaptive control of a dc–dc converter. The proposed technique is based on a simple adaptive filter method and uses a one-tap finite impulse response (FIR) prediction error filter (PEF). The method is computationally efficient and based around a dichotomous coordinate descent (DCD) algorithm. The DCD-recursive least squares (RLS) algorithm has been employed as the adaptive PEF to reduce the computational complexity of existing RLS algorithms for efficient hardware implementation. Results show that the DCD-RLS is able to improve the dynamic performance and convergence rate of the adaptive gains (filter taps) within the controller. In turn, this yields a significant improvement in the overall dynamic performance of the closed-loop control system, particularly in the event of abrupt parameter changes. The proposed controller uses an adaptive proportional–derivative+integral (PD +I) structure which, alongside the DCD algorithm, offers an effective substitute to a conventional proportional–integral–derivative (PID) controller. The nonadaptive integral controller (+I), introduced in the feedback loop, increases the excitation of the filter tap weight and ensures good regulation. The approach results in a fast adaptive controller with self-loop compensation. This is required to minimize the prediction error signal and, in turn, minimize the voltage error signal in the loop by automatically calculating the optimal pole locations. The prediction error signal is further minimized through a second-stage FIR filter (adaptation gain stage). This ensures that the adaptive gains converge to their optimal value. This paper presents detailed simulation analysis and experimental validation on a prototype synchronous dc–dc buck converter. The experimental results clearly demonstrate the superior dynamic performance and voltage regulation compared to conventional PID and adaptive LMS control schemes, with only a modest increase in the computational burden to the microprocessor. [ABSTRACT FROM AUTHOR]

Most of the calculations in standard sphere decoders are redundant in the sense that they either calculate quantities that are never used or calculate some quantities more than once. A new method, which is applicable to lattices as well as finite constellations, is proposed to avoid these redundant calculations while still returning the same result. Pseudocode is given to facilitate immediate implementation. Simulations show that the speed gain with the proposed method increases linearly with the lattice dimension. At dimension 60, the new algorithms avoid about 75% of all floating-point operations. [ABSTRACT FROM AUTHOR]

We demonstrate that flow line models with deterministic service times and an arbitrary arrival process may be exactly decomposed into segments that each exhibit similar behavior. We call the segments channels and demonstrate that this decomposition leads to a recursion for the delay experienced by customers within the system. The consequence, in addition to clearly elucidating the manner in which customers advance, is that the state of a flowline at any time can be completely characterized by a handful of parameters per channel. The recursions and channel decomposition allow us to model a class of state dependent failures that are common in certain cluster tools in semiconductor wafer manufacturing. Using the fact that wafers are typically grouped into batches, we are able to reduce the computation required to simulate the wafer advancement by about 50 times. The models have been tested with data from a clustered photolithography tool in production and provide throughput and process time predictions within 0.5% and3%of the actual performance, respectively. [ABSTRACT FROM AUTHOR]

Recursion is a fundamental computation mechanism which has been incorporated into the SQL language. This work focuses on the optimization of linear recursive queries in SQL. Query optimization is studied with two important graph problems: computing the transitive closure of a graph and getting the power matrix of its adjacency matrix. We present SQL implementations for two fundamental algorithms: Seminaive and Direct. Five query optimizations are studied: 1) Storage and indexing; 2) early selection; 3) early evaluation of nonrecursive joins; 4) pushing duplicate elimination; and 5) pushing aggregation. Experiments compare both evaluation algorithms and systematically evaluate the impact of optimizations with large input tables. Optimizations are evaluated on four types of graphs: binary trees, lists, cyclic graphs, and complete graphs, going from the best to worst case. In general, Seminaive is faster than Direct, except for complete graphs. Storing and indexing rows by vertex and pushing aggregation work well on trees, lists, and cyclic graphs. Pushing duplicate elimination is essential for complete graphs, but slows computation for acyclic graphs. Early selection with equality predicates significantly accelerates computation for all types of graphs. [ABSTRACT FROM AUTHOR]

In this paper, we propose a low-complexity decision-directed channel-estimation scheme, which offers improved performance for space-frequency-block-coded orthogonal frequency-division multiplexing (SFBC-OFDM) systems under doubly selective (i.e., frequency selective and fast fading) channels. First, we propose a square-root-free inverse-QR-decomposition-based groupwise recursive (SIQR-GR) channel-estimation algorithm employing sequences of scaled Givens rotations. The proposed SIQR-GR scheme recursively processes data decisions corresponding to the SFBC groups within each OFDM block to improve system performance under doubly selective channels. Furthermore, the avoidance of square roots and the utilization of scaled Givens rotations ensure that the proposed SIQR-GR scheme is computationally efficient. Second, we derive semi-analytical expressions for the normalized mean square error (NMSE) performance of SIQR-GR and verify the accuracy of the NMSE analysis via numerical simulations. Finally, we provide performance and complexity comparisons between SIQR-GR and previously proposed schemes. These comparisons show an excellent performance-complexity tradeoff achieved by SIQR-GR over the previous solutions under various channel conditions. [ABSTRACT FROM AUTHOR]

The establishment of a localization system is an important task in wireless sensor networks. Due to the geographical correlation between sensed data, location information is commonly used to name the gathered data and address nodes and regions in data dissemination protocols. In general, to estimate its location, a node needs the position information of at least three reference points (neighbors that know their positions). In this work, we propose a different scheme in which only two reference points are required in order to estimate a position. To choose between the two possible solutions of an estimate, we use the known direction of the recursion. This approach leads to a recursive localization system that works with low-density networks (increasing by 40 percent the number of nodes with estimates in some cases), reduces the position error by almost 30 percent, requires 37 percent less processor resources to estimate a position, uses fewer beacon nodes, and also indicates the node position error based on its distance to the recursion origin. No GPS-enabled node is required, since the recursion origin can be used as a relative coordinate system. The algorithm's evaluation is performed by comparing it with a similar localization system; also, experiments are made to evaluate the impact of both systems in geographic algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for learning in structured domains (SDs) using a constructive neural network for graphs (NN4G). The new model allows the extension of the input domain for supervised neural networks to a general class of graphs including both acyclic/cyclic, directed/undirected labeled graphs. In particular, the model can realize adaptive contextual transductions, learning the mapping from graphs for both classification and regression tasks. In contrast to previous neural networks for structures that had a recursive dynamics, NN4G is based on a constructive feedforward architecture with state variables that uses neurons with no feedback connections. The neurons are applied to the input graphs by a general traversal process that relaxes the constraints of previous approaches derived by the causality assumption over hierarchical input data. Moreover, the incremental approach eliminates the need to introduce cyclic dependencies in the definition of the system state variables. In the traversal process, the NN4G units exploit (local) contextual information of the graphs vertices. In spite of the simplicity of the approach, we show that, through the compositionality of the contextual information developed by the learning, the model can deal with contextual information that is incrementally extended according to the graphs topology. The effectiveness and the generality of the new approach are investigated by analyzing its theoretical properties and providing experimental results. [ABSTRACT FROM AUTHOR]

Finding the cross correlation between two m-sequences {st} and {sdt} of the same period 2m - 1, that differ by a decimation d, has been a popular research problem since the 1960s. Many cases with three- and four-valued correlation have been determined. Several values of d are known to lead to five-valued cross correlation but their exact correlation distribution has been open. The correlation distribution is completely determined for one of these families with five-valued cross correlation by using evaluations of certain exponential sums including. Kloosterman sums. The decimation considered is the special decimation d = "Multiple line equation(s) cannot be represented in ASCII text" where m is odd and k = 1, i.e., d = 5/3. The paper introduces some techniques that may be useful to obtain further results on related decimations. [ABSTRACT FROM AUTHOR]

Frequency hopping (FH) sequences play a key role in frequency hopping spread spectrum communication systems. In order to evaluate the performance of FH sequences, Lempel and Greenberger (1974) and Peng and Fan (2004) derived lower bounds on their Hamming auto- and cross-correlations. In this paper, we construct families of FH sequences with Hamming correlations meeting those bounds by combinatorial and algebraic techniques. We first construct optimal families consisting of a single FH sequence with maximum Hamming correlation equal to 2 from a combinatorial approach. Then we investigate families consisting of multiple FH sequences. We provide a combinatorial characterization for such families, and present a recursive method to construct them by means of this characterization. We also describe two algebraic constructions for such families of FH sequences, gerteralizing those of Ding, Moisio, and Yuan (2007). As a consequence, many new optimal families of FH sequences are obtained. [ABSTRACT FROM AUTHOR]

Differential space-time modulation (DSTM) has been recently proposed by Hughes, and Hochwald and Sweldens when the channel information is not known at the receiver, where the demodulation is in fact the same as the coherent demodulation of space-time block coding by replacing the channel matrix with the previously received signal matrix. On the other hand, the DSTM also needs a recursive memory of a matrix block at the encoder and therefore provides a trellis structure when the channel information is known at the receiver, which is the interest of this paper. This recursive structure of the DSTM has been adopted lately by Schlegel and Grant in joint with a conventional binary code and joint iterative decoding/demodulation with a superior performance. The number of states of the trellis from the recursive structure depends on both the memory size, which is fixed in this case, and the unitary space-time code (USTC). When a USTC for the DSTM forms a group, the number of states is the same as the size of the USTC, otherwise the number of the states is the size of the semi-group generated by the USTC from all the multiplications of the matrices in the USTC. It is well known in the conventional convolutional coding (CC) or the trellis coded modulation (TCM), the free (Hamming or Euclidean) distance (or the performance) increases when the number of states increases by adding more memory with a properly designed CC or TCM. In this paper, we systematically study and design the USTC/DSTM for the recursive space-time trellis modulation and show that the diversity product increases when the number of states increases, which is not because of the memory size but because of the different USTC designs that generate different sizes of semi-groups. We propose a new USTC design criterion to ensure that the trellis structure improves the diversity product over the USTC as a block code. Based on the new criterion, we propose a new class of USTC design for an arbitrary number of transmit antennas that has an analytical diversity product formula for two transmit antennas. We then follow Schlegel and Grant's approach for joint encoding and iterative decoding of a binary coded DSTM (turbo space-time coding) and numerically show that our new USTC designs for the recursive space-time trellis modulation outperforms the group USTC used by Schlegel and Grant. [ABSTRACT FROM AUTHOR]

We present a particle filter construction for a system that exhibits time-scale separation. The separation of time scales allows two simplifications that we exploit: 1) the use of the aver- aging principle for the dimensional reduction of the dynamics for each particle during the prediction step and 2) the factorization of the transition probability for the Rao-Blackwellization of the update step. The resulting particle filter is faster and has smaller variance than the particle filter based on the original system. The method is tested on a multiscale stochastic differential equation and on a multiscale pure jump diffusion motivated by chemical re- actions. [ABSTRACT FROM AUTHOR]

It is shown analytically that the multi-target multi- Bernoulli (MeMBer) recursion, proposed by Mahler, has a significant bias in the number of targets. To reduce the cardinality bias, a novel multi-Bernoulli approximation to the multi-target Bayes recursion is derived. Under the same assumptions as the MeMBer recursion, the proposed recursion is unbiased. In addition, a sequential Monte Carlo (SMC) implementation (for generic models) and a Gaussian mixture (GM) implementation (for linear Gaussian models) are proposed. The latter is also extended to accommodate mildly nonlinear models by linearization and the unscented transform. [ABSTRACT FROM AUTHOR]

We consider iterative subspace Wiener filters for solving minimum mean-squared error (MMSE) and minimum variance unbiased estimation problems in low-dimensional subspaces. In this class of subspace filters, the conjugate direction and multistage Wiener filters comprise two large subclasses, and within these the conjugate gradient and orthogonal multistage Wiener filters are the most prominent. We establish very general equivalences between conjugate direction and multistage Wiener filters, wherein the direction vectors of a conjugate direction filter and the stagewise vectors of a multistage filter are related through a one-term autoregressive recursion. By virtue of this recursion, the expanding subspaces of the two filters are identical, even though their bases for them are different. As a consequence, their subspace filters, gradients, and MSEs are identical at each stage of the subspace iteration. If the conjugate direction filter is a conjugate gradient filter, then the equivalent stagewise filter is an orthogonal multistage filter, and vice-versa. If either the conjugate gradient filter or the orthogonal multistage filter is initialized at the cross-covariance vector between the signal and the measurement, then each of the subspace filters iteratively turns out a basis for a Krylov subspace. [ABSTRACT FROM AUTHOR]

Risk-sensitive filters (RSF) put a penalty to higher-order moments of the estimation error compared to conventional filters as the Kalman filter minimizing the mean square error (MSE). The result is a more cautious filter, which can be interpreted as an implicit and automatic way to increase the state noise covariance. On the other hand, the process of jittering, or roughening, is well known in particle filters to mitigate sample impoverishment. The purpose of this contribution is to introduce risk-sensitive particle filters (RSPF) as an alternative approach to mitigate sample impoverishment based on constructing explicit risk functions from a general class of factorizable functions. It is first shown that RSF can be done in nonlinear systems using a recursion of an infinite dimensional information state which involves general risk functions. Then, this information state calculation is carried out using particle approximations. Some alternative approaches, generalizations, specific cases, comparison to existing methods of sample impoverishment mitigation and issues related to the selection of risk functions and parameters are examined. Performance of the resulting filter using various risk functions is illustrated on a simulated scenario and compared with the roughening method. [ABSTRACT FROM AUTHOR]

This paper presents a novel and mathematically rigorous Bayes' recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clutter. Our Bayesian formulation is mathematically well-founded due to our use of a consistent likelihood function derived from random finite set theory. It is established that under certain assumptions, the proposed Bayes' recursion reduces to the cardinalized probability hypothesis density (CPHD) recursion for a single target. A particle implementation of the proposed recursion is given. Under linear Gaussian and constant sensor field of view assumptions, an exact closed-form solution to the proposed recursion is derived, and efficient implementations are given. Extensions of the closed-form recursion to accommodate mild nonlinearities are also given using linearization and unscented transforms. [ABSTRACT FROM AUTHOR]

In this paper, a new algorithm to efficiently compute the two-dimensional wavelet transform is presented. This algorithm aims at low memory consumption and reduced complexity, meeting these requirements by means of line-by-line processing. In this proposal, we use recursion to automatically place the order in which the wavelet transform is computed. This way, we solve some synchronization problems that have not been tackled by previous proposals. Furthermore, unlike other similar proposals, our proposal can be straightforwardly implemented from the algorithm description. To this end, a general algorithm is given which is further detailed to allow its implementation with a simple filter bank or using the more efficient lifting scheme. We also include a new fast run-length encoder to be used along with the proposed wavelet transform for fast image compression and reduced memory consumption. When a 5-megapixel image is transformed, experimental results show that the proposed wavelet transform requires 200 times less memory and is five times faster than the regular one. If we consider the whole coding system, numerical results show that it achieves state-of-the-art performance with very low memory requirements and fast execution, becoming an interesting solution for resource-constrained devices such as mobile phones, digital cameras, and PDAs. [ABSTRACT FROM AUTHOR]

This paper proposes two noniterative approaches to solve a symmetric linear system associated with the fast affine projection adaptation algorithm. The first approach, using matrix LDLT factorization, can provide an exact solution at a moderate complexity, in contrast with the fact that existing stable approaches are all approximate. Based on a reciprocating recursion scheme, the second approach has a very low complexity and gives a good approximate solution. Steady-state and transient properties of the proposed and certain previous FAP algorithms are studied in detail. Being stable and optimal under all step size conditions, fast affine projection algorithms incorporating the proposed approaches are promising in telecom and other applications of adaptive filtering. [ABSTRACT FROM AUTHOR]

This paper presents information filters in Riccati recursions and in array algorithms for descriptor systems subject to parameters uncertainties. The filters are developed in filtered and predicted forms. The inversion of the state matrix is avoided in the new information recursive formulas. Therefore, it turns out clear that the invertibility of the state matrix, usually considered in the state-space information recursions, is not necessary. A numerical example is provided to illustrate the performance of the proposed robust array algorithms. [ABSTRACT FROM AUTHOR]

In this correspondence, new characterizations for the construction of zero correlation zone (ZCZ) sequences from mutually orthogonal Golay complementary sets (MOGCS) is presented. It is shown that the recursive construction of MOGCS is inherent in these characterization. Previously known constructions of ZCZ sequences and MOGCS are shown to be special cases of this characterization. The notion of mutually orthogonal ZCZ sequence sets is also introduced. [ABSTRACT FROM AUTHOR]

This correspondence addresses several practical problems in implementing a forward-backward (FB) algorithm for an explicit-duration hidden Markov model. First, the FB variables are redefined in terms of posterior probabilities to avoid possible underflows that may occur in practice. Then, a forward recursion is used that is symmetric to the backward one and can reduce the number of logic gates required to implement on a field-programmable gate-array (FPGA) chip. [ABSTRACT FROM AUTHOR]

In this paper, three generic RAM-based architectures are proposed to efficiently construct the corresponding two-dimensional architectures by use of the line-based method for any given hardware architecture of one-dimensional (1-D) wavelet filters, including conventional convolution-based and lifting-based architectures. An exhaustive analysis of two-dimensional architectures for discrete wavelet transform in the system view is also given. The first proposed architecture is for 1-level decomposition, which is presented by introducing the categories of internal line buffers, the strategy of optimizing the line buffer size, and the method of integrating any 1-D wavelet filter. The other two proposed architectures are for multi-level decomposition. One applies the recursive pyramid algorithm directly to the proposed 1-level architecture, and the other one combines the two previously proposed architectures to increase the hardware utilization. According to the comparison results, the proposed architecture outperforms previous architectures in the aspects of lint buffer size, hardware cost, hardware utilization, and flexibility. [ABSTRACT FROM AUTHOR]

A scale-adaptive filtering scheme is developed for underspread channels based on a model of the linear time-varying channel operator as a process in scale. Recursions serve the purpose of adding detail to the filter estimate until a suitable measure of fidelity and complexity is met. Resolution of the channel impulse response associated with its coherence time is naturally modeled over the observation time via a Gaussian mixture assignment on wavelet coefficients. Maximum likelihood, approximate maximum a posteriori (MAP) and posterior mean estimators, as well as associated variances, are derived. Doppler spread estimation associated with the coherence time of the filter is synonymous with model order selection and a MAP estimate is presented and compared with Laplace's approximation and the popular AIC. The algorithm is implemented with conjugate-gradient iterations at each scale, and as the coherence time is recursively decreased, the lower scale estimate serves as a starting point for successive reduced-coherence time estimates. The algorithm is applied to a set of simulated sparse multipath Doppler spread channels, demonstrating the superior MSE performance of the posterior mean filter estimator and the superiority of the MAP Doppler spread stopping rule. [ABSTRACT FROM AUTHOR]

we propose an embedded, block-based, image wavelet transform coding algorithm of low complexity. it uses a recursive set-partitioning procedure to sort subsets of wavelet coefficients by maximum magnitude with respect to thresholds that are integer powers of two. It exploits two fundamental chars acteristics of an image transform-the well-defined hierarchical structure, and energy clustering in frequency and in space. The two partition strategies allow for versatile and efficient coding of several image transform structures, including dyadic, blocks inside subbands, wavelet packets, and discrete cosine transform (DCT). We describe the use of this coding algorithm in several implementations, including reversible (lossless) coding and its adaptation for color images, and show extensive comparisons with other state-of-the-an coders, such as set partitioning in hierarchical trees (SPIlT) and JPEG2000, We conclude that this algorithm, in addition to being very flexible, retains alt the desirable features of these algorithms and is highly competitive to them in compression efficiency. [ABSTRACT FROM AUTHOR]

A method to estimate the drop size distribution (DSD) parameters for dual-frequency radar observations that does not rely on the surface echoes is proposed. The method adjusts the estimates of attenuation factor at the surface iteratively until these estimates retrieve the reflectivity factors that are equal to the original measured reflectivity factors. In this iteration method, the backward-recursion equations are used as a main routine to calculate the DSD parameters for each range bin. The estimates of attenuation factor at the surface are obtained from these DSD parameters. The method is applied to the airborne radar data from the CaPE experiment in 1991. The comparison between the results derived from the surface reference technique and those derived from the proposed method is presented and discussed. [ABSTRACT FROM AUTHOR]

We introduce a new tower field representation, optimal tower fields (OTFs), that facilitates efficient finite field operations. The recursive direct inversion method we present has significantly lower complexity than the known best method for inversion in optimal extension fields (OEFs), i.e., Itoh-Tsujii's inversion technique. The complexity of our inversion algorithm is shown to be O(m²), significantly better than that of the ltoh-Tsujii algorithm, i.e., O(m²(log2 m)). This complexity is further improved to O(mlog2 3) by utilizing the Karatsuba-ofman algorithm. In addition, we show that OTFs may be converted to OEF representation via a simple permutation of the coefficients and, hence, OTF operations may be utilized to achieve the OEF arithmetic operations whenever a corresponding OTF representation exists. While the original OTF multiplication and squaring operations require slightly more additions than their OEF counterparts, due to the free conversion, both OTF operations may be achieved with the complexity of OEF operations. [ABSTRACT FROM AUTHOR]

This paper proposes a new structure for split transversal filtering and introduces the optimum split Wiener filter. The approach consists of combining the idea of split filtering with a linearly constrained optimization scheme. Furthermore, a continued split procedure, which leads to a multisplit filter structure, is considered. It is shown that the multisplit transform is not an input whitening transformation. Instead, it increases the diagonalization factor of the input signal correlation matrix without affecting its eigenvalue spread. A power normalized, time-varying step-size least mean square (LMS) algorithm, which exploits the nature of the transformed input correlation matrix, is proposed for updating the adaptive filter coefficients. The multisplit approach is extended to linear-phase adaptive filtering and linear prediction. The optimum symmetric and antisymmetric linear-phase Wiener filters are presented. Simulation results enable us to evaluate the performance of the multisplit LMS algorithm. [ABSTRACT FROM AUTHOR]

An analytical method for approximate performance evaluation of binary linear block codes using an additive white Gaussian noise channel model with binary phase-shift keying modulation is presented. We focus on the probability density function of the bit log-likelihood ratio (LLR), which is expressed in terms of the Gram-Charlier series expansion. This expansion requires knowledge of the statistical moments of the bit LLR. We introduce an analytical method for calculating these moments. This is based on some recursive calculations involving certain weight enumerating functions of the code. It is proved that the approximation can be as accurate as desired, if we use enough terms in the Gram-Charlier series expansion. Numerical results are provided for some examples, which demonstrate close agreement with simulation results. [ABSTRACT FROM AUTHOR]

A novel sequential estimation method is proposed for the initial synchronization of pseudonoise (PN) signals derived from m-sequences. This sequential estimation method is designed based on the principle of recursive soft-in/soft-out (SISO) decoding, and we refer to it as the recursive soft sequential estimation (RSSE) acquisition scheme. The RSSE acquisition scheme exhibits a complexity similar to that of a conventional m-sequence generator, which increases only linearly with the number of stages in the m-sequence generator. Our simulation results also show that the acquisition time of the proposed RSSE acquisition scheme is also Linearly dependent on the number of stages in the m-sequence generator. Owing to the above properties, the employment of the proposed RSSE acquisition scheme is beneficial for the acquisition of long m-sequences. [ABSTRACT FROM AUTHOR]

Examines the generated maximal-length linear congruential sequences. Use of simple recursion to generate bipartite graph of a low-density parity-check code; Description of the graph structures of the codes; Highlights of the simulation results.

Reviews a method to determine the distribution of the zeros of a polynomial with respect to the unit-circle unhampered by nonessential singularities. Aim of the unit-circle zero location problem; Form of the recursion and the rule to obtain the zero distribution in the nonsingular case; Completion of the method into a general zero location theorem.

Demonstrates that the performance of classification trees based on recursive designs can be inferior to those based on global designs. Tree-structured classification; Testing strategies; Bounds on the information gain; Experiments and discussion.

Presents a recursive formula for the moments of phase noise in communication systems. Functional of the Brownian motion; Applications of the moments obtained by the recursion; Conclusions.

Presents information on quantum electronics, using the Green's function and the recursion methods to calculate the tunneling lifetime of a particle in a quantum well (QW). Information on the projected Green's function; Details on the recursion method; Conclusion reached on the calculation.

A multiple linear (ML) recursion is a recursion which consists of multiple linear recursive rules and one or more nonrecursive rules. ML recursions can be classified into two classes: side-coherent and non-side-coherent. This paper studies the efficient evaluation of side-coherent ML recursions, which can be further classified into three types: (I) multiple one- sided, (II) multiple balanced k-sided, and (III) multiple mixed k-sided. New techniques are developed by integrating the existing single-linear recursive query evaluation methods with the idea of side-relation unioned processing, which leads to a set of efficient query evaluation algorithms such as a side-relation unioned transitive closure algorithm for the processing of Type I ML recursions, and a generalized side-relation unioned magic sets method for the processing of Types II and III ML recursions. Therefore the evaluation of ML recursions can be mapped to the framework of the evaluation of single linear recursions. Previously developed techniques for the evaluation of single linear recursions, such as the selection of processing strategies for queries with complex instantiations and inquiries, can be applied to the evaluation of ML recursions as well. [ABSTRACT FROM AUTHOR]

According to the static locking concurrency control policy, transactions which have predeclared their locks can only be activated when they have acquired all requested locks. Lock contention results in transaction blocking, such that only a subset of V transactions available for processing can be active. We develop an analytic solution method based on recursion to compute performance measures of interest for static locking systems. The probability of lock conflict is computed approximately by noting that the mean number of active transactions encountered by a blocked transaction is that of a system with V - 1 transactions. Transactions delay before activation is determined by the mean number of times it is checked unsuccessfully for activation (e( V )) and the mean elapsed time between these instants. It is shown that the mean number of active transactions is V/(1 + η(V)), where η is the ratio of the mean residual residence time of a transaction in the system and its mean residence time. It follows that the variability in transaction residence time, in addition to lock contention, has an adverse effect on performance. Based on the locking requirements of transactions, five database access models are considered: 1) a fixed number of exclusive locks, 2) a variable number of exclusive locks, 3) shared in addition to exclusive lock requests, 4) query and update transactions, 5) nonuniform database accesses in which transactions access objects in different database domains. Numerical results obtained by the analytical solution are validated against simulation results and shown to be quite accurate. They are also used to gain insight into the behavior of static locking systems. These insights are summarized at the end of the paper. [ABSTRACT FROM AUTHOR]