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So far, the problem of unmixing large or multitemporal hyperspectral data sets has been specifically addressed in the remote sensing literature only by a few dedicated strategies. Among them, some attempts have been made within a distributed estimation framework, in particular, relying on the alternating direction method of multipliers. In this paper, we propose to study the interest of a partially asynchronous distributed unmixing procedure based on a recently proposed asynchronous algorithm. Under standard assumptions, the proposed algorithm inherits its convergence properties from recent contributions in nonconvex optimization, while allowing the problem of interest to be efficiently addressed. Comparisons with a distributed synchronous counterpart of the proposed unmixing procedure allow its interest to be assessed on synthetic and real data. Besides, thanks to its genericity and flexibility, the procedure investigated in this paper can be implemented to address various matrix factorization problems. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of maximizing the minimum power gain in a wide main lobe for an array antenna. To obtain the desired power gain pattern, current literatures solve the problem known as shaped beam pattern synthesis (SBPS) by setting the beam pattern expression as the cost function. The power gain in a certain direction of the array antenna is comprehensively decided by the array radiated power density and the total radiated power. Both these two parameters are affected by the selection of array elements’ weights. However, the SBPS-based methods do not take the total radiated power into account. Therefore, the SBPS-based methods cannot obtain the power gain pattern directly, and the optimal power gain pattern, consequently, cannot be guaranteed. To overcome this deficiency, this paper maximizes the minimum power gain in the desired wide main lobe by directly setting the power gain expression as the cost function. Aiming at optimizing the cost function, this paper first sets up a power gain optimization problem which has concave form. Termed this optimization problem as the power gain pattern synthesis (PGPS) problem. The concave PGPS problem is then converted to a series of convex subproblems and an iterative algorithm is proposed to solve it efficiently. Solution to the PGPS problem is proven to be able to achieve higher minimum power gain in a desired wide main lobe than the results from the SBPS-based algorithms. Simulations are carried out with both linear array antenna and planar array antenna. Comparisons with the existed SBPS-based algorithms validate the effectiveness and advantages of the proposed PGPS-based algorithm. In addition, further improvement on suppressing the sidelobe level for the PGPS problem is discussed. [ABSTRACT FROM AUTHOR]

The multipeaked correlation functions of binary offset carrier (BOC) modulated signals introduce an ambiguity threat into the code tracking. Several techniques have been proposed to solve this problem, such as a class of two-dimensional (2-D) tracking techniques, in which the spreading code and the subcarrier are tracked separately. In this paper, the key properties of correlation functions and the theoretical tracking performance analysis considering noise and multipath environments of the general 2-D tracking loop are studied. Exact explicit expressions, taking into account the effects of local subcarrier waveform mismatching and the front-end bandlimiting, are provided for the correlation function employed in 2-D tracking. From these expressions, the key characteristics of 2-D correlation functions such as the shape, coupling relation between dimensions, and the effects of bandlimiting can be clearly seen. Moreover, general theoretical methods to predict the performance of the 2-D tracking techniques under the multipath and noise environments are provided. The results obtained in this paper can facilitate investigations in the area of 2-D tracking technique parameter optimization and performance assessment. [ABSTRACT FROM PUBLISHER]

Many signal processing applications require estimation of time-varying sparse signals, potentially with the knowledge of an imperfect dynamics model. In this paper, we propose an algorithm for dynamic filtering of time-varying sparse signals based on the sparse Bayesian learning (SBL) framework. The key idea underlying the algorithm, termed SBL-DF, is the incorporation of a signal prediction generated from a dynamics model and estimates of previous time steps into the hyperpriors of the SBL probability model. The proposed algorithm is online, robust to imperfect dynamics models (due to the propagation of dynamics information through higher-order statistics), robust to certain undesirable dictionary properties such as coherence (due to properties of the SBL framework), allows the use of arbitrary dynamics models, and requires the tuning of fewer parameters than many other dynamic filtering algorithms do. We also extend the fast marginal likelihood SBL inference procedure to the informative hyperprior setting to create a particularly efficient version of the SBL-DF algorithm. Numerical simulations show that SBL-DF converges much faster and to more accurate solutions than standard SBL and other dynamical filtering algorithms. In particular, we show that SBL-DF outperforms state of the art algorithms when the dictionary contains the challenging coherence and column scaling structure found in many practical applications. [ABSTRACT FROM AUTHOR]

The transverse oscillation (TO) technique can improve the estimation of tissue motion perpendicular to the ultrasound beam direction. TOs can be introduced using plane wave (PW) insonification and bilobed Gaussian apodization (BA) on receive (abbreviated as PWTO). Furthermore, the TO frequency of PWTO can be doubled after a heterodyning demodulation process is performed (abbreviated as PWTO*). This paper is concerned with identifying the limitations of the PWTO technique in the specific context of myocardial deformation imaging with phased arrays and investigating the conditions in which it remains advantageous over traditional focused (FOC) beamforming. For this purpose, several tissue phantoms were simulated using Field II, undergoing a wide range of displacement magnitudes and modes (lateral, axial, and rotational motions). The Cramer-Rao lower bound was used to optimize TO beamforming parameters and theoretically predict the fundamental tracking performance limits associated with the FOC, PWTO, and PWTO* beamforming scenarios. This framework was extended to also predict the performance for BA functions that are windowed by the physical aperture of the transducer, leading to higher lateral oscillations. It was found that windowed BA functions resulted in lower jitter errors compared with traditional BA functions. PWTO* outperformed FOC at all investigated signal-to-noise ratio (SNR) levels but only up to a certain displacement, with the advantage rapidly decreasing when the SNR increased. These results suggest that PWTO* improves lateral tracking performance, but only when interframe displacements remain relatively low. This paper concludes by translating these findings into a clinical environment by suggesting optimal scanner settings. [ABSTRACT FROM PUBLISHER]

Passive source localization is an important research area with numerous applications in mobile communications and signal processing. This paper presents an analysis of energy-based localization performance with unknown transmit power using received signal strength (RSS) and RSS difference (RSSD) models. These models are widely used because of their low cost and simple implementation. Previous studies were based on the assumption that the source node transmit power is known, which is not practical in many situations. The Cramér–Rao lower bound for the RSS and RSSD models with correlated noise is derived as a performance benchmark for the mean squared error (MSE) of the location and transmit power estimation. It is shown that the MSE can be factored into two independent terms corresponding to the geometric distribution of the sensors and the channel parameters including the noise variance. The effect of the sensor and source node positions on the location accuracy and the MSE is derived via the geometric dilution of precision (GDOP). The GDOP is then used to evaluate the effect of the joint estimation of unknown power and source location on the performance. Lower bounds on the GDOP are derived to obtain the minimum MSE. The RSSD solution is obtained by formulating the nonlinear and nonconvex objective functions into a convex optimization problem through relaxation and semidefinite programming. Simulation results are presented with the source inside or outside the sensor network. [ABSTRACT FROM AUTHOR]

Condition monitoring and fault diagnosis (CMFD) of key moving sources has attracted more and more attentions in recent years. Among many CMFD strategies, the wayside acoustic signal-based method can detect slight failure efficiently in time with a low-cost system. However, the nonlinear time-varying distance between the moving source and the microphone array would bring in serious Doppler distortion in the acquired signals. The Doppler distortion would result in serious amplitude distortion, frequency shift, and band extension, which is an obstacle for accurate CMFD. Considering the superior time-spatial characteristics of circular microphone array, this paper presents a short-time sparse singular value decomposition (SSVD) method based on wayside circular microphone array signals to eliminate the existed Doppler distortion. The procedure of the presented method is summarized as follows. First, the Doppler distortion array signals are decomposed into a series of array segments with a sliding window. Afterward, the corresponding moving angles (MAs) of each array segments are calculated with the introduced SSVD method. Finally, the fitting time-varying MA curve and time-domain interpolation resampling are employed to eliminate the Doppler distortion. Simulation results validated that the proposed method could achieve better localization accuracy under heavy background noise as compared to other traditional methods. Moreover, the effectiveness of the proposed method has been further verified with real experiments, which indicates excellent potential application prospects for moving vehicles, trains, planes, and so on. [ABSTRACT FROM AUTHOR]

In visible light communication (VLC), using multiple colors is an efficient way to enhance data rate, leading to multi-color VLC (MC-VLC). However, the performance of MC-VLC is jeopardized by the spectral overlaps of different colors. Thin-film optical filters, as the key component of MC-VLC systems, are usually adopted to separate colors. The passband bandwidth (BW) and center wavelength (CWL) of optical filters are critical to mitigate the crosstalk among colors and, thus, must be carefully designed. Moreover, due to the intrinsic wavelength shift of the CWL with the varying of the angle of incidence, it is challenging to support mobility for MC-VLC. In this paper, we consider a joint design of multiple optical filters for MC-VLC by properly selecting the BW and CWL of each filter. We first investigate the optical filter design for a fixed receiver location. Then, to support mobility, we propose two robust optical filter designs, namely, statistically and worst case robust designs, which do not rely on the exact receiver location. Efficient methods are developed to solve the corresponding design problems and obtain the optimized optical filters. Compared with the existing optical filters, the proposed optical filters exhibits much better performance in various scenarios. [ABSTRACT FROM AUTHOR]

In the scenario of frequency coexistence between the geostationary (GEO) and non-geostationary (NGEO) satellite networks, the NGEO system should not incur harmful interference to the GEO system according to the policy of the Radio Regulations. Therefore, spectrum sensing as a promising solution is applied widely in this scenario. With the increasing number of NGEO satellites in the space, one NGEO system could be affected by other NGEO systems while sensing the signal from the GEO system. Given these preconditions, the cognitive radio scenario considered in this paper is that: the GEO system is regarded as the primary user, one NGEO system is regarded as the secondary user, and another NGEO system is regarded as the interfering user. Meanwhile, all the satellite systems are supposed to operate with more than one discrete transmit power levels, which is practical and fits the concept of adaptive power control. In our context, we propose a spectrum strategy using hypothesis testing as well as maximum a posteriori to differentiate the GEO signal from the interfering NGEO and noise, and then identify the specific power level utilized by the GEO system. Moreover, we derive the closed-form expressions for threshold of verifying the status of the GEO and for decision regions to determine its power level. Finally, extensive simulations are provided to verify the proposed studies. [ABSTRACT FROM AUTHOR]

This paper studies the problem of learning under both large datasets and large-dimensional feature space scenarios. The feature information is assumed to be spread across agents in a network, where each agent observes some of the features. Through local cooperation, the agents are supposed to interact with each other to solve an inference problem and converge towards the global minimizer of an empirical risk. We study this problem exclusively in the primal domain, and propose new and effective distributed solutions with guaranteed convergence to the minimizer with linear rate under strong convexity. This is achieved by combining a dynamic diffusion construction, a pipeline strategy, and variance-reduced techniques. Simulation results illustrate the conclusions. [ABSTRACT FROM AUTHOR]

Intentional jammers broadcasting chirp-style signals present a major threat to the operation of the global navigation satellite systems (GNSS) receivers. The time–frequency (TF) domain method based on the subspace projection technique is a common countermeasure against jamming. However, it is sensitive to inaccuracies in the instantaneous frequency (IF) estimates when dealing with jammers with rapidly changing frequency characteristics. In this paper, an approach for chirp-style jamming signal suppression in GNSS receivers using an adaptive-partitioned subspace projection is developed, which is insensitive to IF estimation errors. We first propose to choose the TF observation window length based on the jammer sweep rate and displace the IF estimates by a spectral bin to handle the resolution errors in the IF estimates. This operation ensures that the instantaneous phase (IP) estimation errors approximately stay constant for the interval that the jammer IF varies linearly upward. Owing to this property, the received data vector is partitioned into adaptive block sizes based on the jammer chirp rate estimates, which reflect the varying IF characteristics. The received signal is then projected onto the jammer orthogonal subspace constructed from the IF estimates according to the adaptive projection blocks. Simulation results indicate the effectiveness of the proposed technique for suppressing chirp-style jammers when compared with other techniques reported in the literature. The proposed approach provides an improvement by up to 11 dB in terms of the correlator signal-to-noise power ratio of the processed signal. [ABSTRACT FROM AUTHOR]

When a possible target is embedded in a low-rank (LR) Gaussian clutter (which is contained in a low-dimensional subspace) plus a white Gaussian noise, the detection process can be performed by applying the LR adaptive normalized matched filter (LR-ANMF), which is a function of the estimated projector. In a recent work, we derived an approximate distribution of the LR-ANMF under the $\mathcal {H}_0$ hypothesis by using a restrictive hypothesis (the target has to be orthogonal to the clutter subspace). In this paper, we propose to determine new approximations of the Pfa and the Pd of the LR-ANMF by relaxing this restrictive hypothesis. This new derivation is based on results concerning the convergence in a large dimension regime of quadratic forms. Simulations validate our result, in particular, when the tested signal is close to the clutter subspace. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for designing a dual-channel balanced filter and a dual-channel balun filter based on the quad-mode dielectric resonator (DR) for the first time. By sharing one common quad-mode DR, two balanced filters or two balun filters are integrated as one single-cavity configuration, featuring compact size and high integration. A cylindrical DR with two short ends is investigated to construct the quad-mode DR. By properly arranging input and output feeding probes, two modes of the DR are only excited by the feeding probes of one channel and the other two modes are excited by that of the other channel. Accordingly, signals cannot be transmitted between the two channels, resulting in high isolation. Moreover, the required out-of-phase characteristics of the balanced and balun filters can be obtained by the inherent electromagnetic field properties of the DR without adding additional circuits, featuring a simple structure. For demonstration, a dual-channel balanced filter and a dual-channel balun filter are designed and fabricated, showing excellent balanced or balun filter performance of each channel as well as high isolation between the two channels. As compared to the other reported DR balanced and balun filters, the proposed designs exhibit a significant size reduction, which are attractive in wireless systems. [ABSTRACT FROM AUTHOR]

The superposition of experimental and analytical data is useful for simulating ultrasonic images of defects in samples containing high levels of coherent structural noise. This technique assumes that the superposition of the response of a defect in a homogeneous medium with that of a heterogeneous, defect-free medium is identical to the response of the same defect embedded in the heterogeneous medium. This implies a single-scattering process. Previous experimental work demonstrated successful use of the technique but only over a limited range of defect signal-to-noise ratios (SNRs). However, there was a concern that it might not remain valid at low SNR due to, for example, multiple-scattering effects. This paper shows that this technique provides accurate results over the full range of SNRs of defects where the defect is discernible from image noise. The technique is, therefore, suitable for simulating any inspection where ultrasonic imaging is an appropriate method of nondestructive evaluation. [ABSTRACT FROM AUTHOR]

This paper presents a new passivity enforcement technique for frequency-dependent network equivalents expressed as rational models. The main feature of the proposed technique is that only a few residues of the rational model are perturbed, so that the passivity enforcement procedure becomes computationally more efficient compared to existing methods. The proposed technique is verified on practical network cases. It is demonstrated that the accuracy of the perturbed model is maintained in frequency-domain fitting and time-domain simulations of transients. [ABSTRACT FROM AUTHOR]

The ever increasing demands for mobile network access have resulted in a significant increase in bandwidth usage. By improving the system spectral efficiency, multi-way relay networks (MWRNs) provide promising approaches to address this challenge. In this paper, we propose a novel linear beamforming design, namely partial zero-forcing (PZF), for MWRNs with a multiple-input-multiple-output relay. Compared to zero-forcing (ZF), PZF relaxes the constraints on the relay beamforming matrix such that only partial user-interference, instead of all, is canceled at the relay. The users eliminate the remaining interferences through self-interference and successive interference cancellation. A sum-rate maximization problem is formulated and solved to exploit the extra degrees-of-freedom resulted from PZF. Simulation results show that the proposed PZF relay beamforming design achieves significantly higher network sum-rates than the existing linear beamforming designs. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel adaptive scheme for full-duplex communication of secondary users (SUs) in a cognitive radio network. The secondary network operates adaptively in three modes; cooperative sensing (CS), full duplex transmit and sensing (FDTS), and in-band bidirectional full duplex transmit and receive (FDTR). In the CS mode, the secondary nodes will detect the signal of a primary user (PU) through a novel cooperative medium access control (MAC) protocol and will decide the system's mode of operation in the subsequent spectrum hole. This adaptive decision is based on dual-threshold detection introduced for the first time. When the PU's signal at SU's receivers is weak, the system switches to the FDTS mode to avoid higher collisions probability and long or endless collision durations. In the FDTS mode, one of SUs senses the PU activity continuously while transmitting to another node. When the channel conditions allow, the system switches to the FDTR mode, in which the SUs would communicate bidirectionally in an asynchronous full duplex manner. The novel idea of asynchronous transmission in this mode will result in decreased maximum and average collision durations. Analytical closed forms for probability of collision, average collision duration, and cumulative collision duration, as well as throughput of the SU network are derived, and performance of the proposed scheme in terms of the above-mentioned metrics, effectiveness, and advantages over conventional methods of sensing and transmission are verified via simulations. [ABSTRACT FROM AUTHOR]

Shingled magnetic recording emerges as a promising near-term option to sustain the historical areal density growth of hard-disk drives while retaining conventional heads and media. Highly scaled shingled magnetic recording is subject to severe intertrack interference, which naturally demands 2-D read channel signal processing. By concurrently detecting multitrack read-back signals from a read head array, joint 2-D signal detection can fully exploit the 2-D interference to maximize the detection performance at the penalty of very high computational complexity. As modern read channel employs iterative signal detection and decoding and hard-disk drives are very cost sensitive, it is highly desirable to effectively reduce the 2-D signal detection computational complexity and hence silicon cost at minimal detection performance loss. This paper presents two low-complexity 2-D soft-output Viterbi algorithm (SOVA) detector design strategies for realizing multitrack joint 2-D detection, which represent different complexity versus performance tradeoffs. By carrying out simulations and application-specific integrated circuit design, this paper shows that, compared with the best symbol-based 2-D SOVA, it is feasible to achieve almost the same detection performance and meanwhile reduce the silicon area by more than 60% in three-track joint detection. [ABSTRACT FROM AUTHOR]

Packaging-induced performance changes of microelectromechanical systems (MEMS) usually are detrimental in the device development. This paper presents a methodology of tuning the force range of a designated MEMS tactile sensor for broader application potentials by packaging this millinewton-level force sensor with different polymers. The force range of the tactile sensor has been enhanced from 30 mN to 400 mN and 100 N, respectively, which are more than tenfolds or 1000 folds of its original capability, by ruggedizing with the polydimethylsiloxane and polyurethane. Numerical analysis and experimental characterization have verified the tuned force range by these two packaging approaches. Three potential applications for the physiological signal monitoring have been revealed by preliminary emulation test results, including emulated lip pressure measurement, heart rate monitoring, and the finger strength evaluation. This methodology sheds light on reconciling the sensitivity changes induced by the packaging phase from defects to merits for broader application potentials in the MEMS development, accelerating the fabrication flow and lowering the cost with the reusability of concurrent devices. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the secure relay beamforming problem for simultaneous wireless information and power transfer (SWIPT) in an amplify-and-forward (AF) two-way relay network. We consider scenarios that the eavesdropper's channel state information (CSI) is and is not available. When the eavesdropper's CSI is available, our objective is to maximize the achievable secrecy sum rate under transmit power constraint and energy harvesting constraint. Since the optimization problem is nonconvex, we derive its performance upper bound, which requires 2-D search, where a semidefinite programming is solved in each step. We also propose an upper bound-based rank-one solution by employing the Gaussian randomization method. To reduce computational complexity, we transform the optimization problem into a difference-of-convex programming and propose a sequential parametric convex approximation (SPCA)-based iterative algorithm to find a locally optimal solution. Furthermore, we also propose a zero-forcing (ZF)-based suboptimal solution. Simulation results demonstrate that the upper bound-based rank-one solution archives the performance almost the same as the upper bound that has high computational complexity. The low-complexity SPCA-based locally optimal solution performs close to the upper bound. The ZF-based suboptimal solution has the lowest computational complexity among the proposed solutions. When the eavesdropper's CSI is not available, we propose an artificial noise-aided secure relay beamforming scheme. [ABSTRACT FROM AUTHOR]

Due to the need for adequate statistically homogeneous training, full-dimensional space-time adaptive processing (STAP) is well accepted to be impractical. Several previous works have addressed this issue by reducing the adaptive degrees of freedom (DoF), in turn reducing the required training. In this paper, we introduce a new multistage STAP approach that significantly reduces the required sample support while still processing all available DoF. The multistage fast fully adaptive (FFA) scheme draws inspiration from the butterfly structure of the fast Fourier transform. It uses a ?divide-and-conquer? approach by creating several smaller STAP problems but then combines the outputs of each problem adaptively as well. The reduction in required sample support rivals currently available reduced DoF algorithms. We also develop three variants of the algorithm, including one that uses random subdivisions of the original STAP problem.We test the efficacy of the algorithms developed via simulations based on simulated airborne radar data and measured high-frequency surface wave radar data. The results show that for simulated homogeneous data, the performance of the FFA approaches is comparable to that of available STAP algorithms; however, with measured data, the FFA approach provides significantly better performance. [ABSTRACT FROM AUTHOR]

This paper presents a stochastic geometry-based framework for the design and analysis of downlink multi-user multiple-input multiple-output (MIMO) heterogeneous cellular networks with linear zero-forcing transmit precoding and receive combining, assuming Rayleigh fading channels and perfect channel state information. The generalized tiers of base stations may differ in terms of their Poisson point process spatial density, number of transmit antennas, transmit power, artificial-biasing weight, and number of user equipments served per resource block. The spectral efficiency of a typical user equipped with multiple receive antennas is characterized using a non-direct moment-generating-function-based methodology with closed-form expressions of the useful received signal and aggregate network interference statistics systematically derived. In addition, the area spectral efficiency is formulated under different space-division multiple-access and single-user beamforming transmission schemes. We examine the impact of different cellular network deployments, propagation conditions, antenna configurations, and MIMO setups on the achievable performance through theoretical and simulation studies. Based on the state-of-the-art system parameters, the results highlight the inherent limitations of baseline single-input single-output transmission and conventional sparse macro-cell deployment, as well as the promising potential of multi-antenna communications and small-cell solution in interference-limited cellular environments. [ABSTRACT FROM AUTHOR]

This paper considers the coherent integration problem for a maneuvering target with complex motions, where the velocity, acceleration, and jerk result in respectively the first-order range migration (FRM), second-order range migration (SRM), and third-order range migration (TRM) within the coherent pulse interval. A new coherent integration algorithm based on generalized keystone transform (KT) and second-order dechirp process is proposed, which employs the third-order KT, six-order KT, second-order KT, and fold factor searching to correct the TRM, SRM, and FRM, respectively. The range migration change during each step and computational complexity are also theoretically analyzed. Compared with the generalized Radon Fourier transform (GRFT) algorithm, the presented method can avoid the blind speed sidelobe (BSSL) and acquire close integration performance but with much lower computational cost. Simulations are provided to demonstrate the effectiveness. Finally, a generalized method, named generalized KT and generalized dechirp process (GKTGDP), is also introduced for the maneuvering target with arbitrary high-order range migration. [ABSTRACT FROM PUBLISHER]

This paper introduces a novel virtual signal injection-based control method for maximum torque per ampere (MTPA) operation of interior permanent magnet synchronous machine (IPMSM) drives. The proposed method injects a small virtual current angle signal mathematically for tracking the MTPA operating point and generating d-axis current command by utilizing the inherent characteristic of the MTPA operation. This method is parameter independent in tracking the MTPA points, and it does not inject any real signal to current or voltage command. Consequently, the problems associated with real high-frequency signal injection, such as increases in copper and iron loss can be avoided. Moreover, it is robust to current/voltage harmonics and motor torque disturbances. The proposed method is verified by simulations and experiments under various operating conditions on a prototype IPMSM drive system. [ABSTRACT FROM AUTHOR]

This paper revisits an existing method of constructing high-dimensional probability density functions (PDFs) based on the PDF at the output of a dimension-reducing feature transformation. We show how to modify the method so that it can provide the PDF with the highest entropy among all PDFs that generate the given low-dimensional PDF. The method is completely general and applies to arbitrary feature transformations. The chain-rule is described for multi-stage feature calculations typically used in signal processing. Examples are given including MFCC and auto-regressive features. Experimental verification of the results using simulated data is provided including a comparison with competing generative methods. [ABSTRACT FROM PUBLISHER]

Compressive sensing (CS) allows for acquisition of sparse signals at sampling rates significantly lower than the Nyquist rate required for bandlimited signals. Recovery guarantees for CS are generally derived based on the assumption that measurement projections are selected independently at random. However, for many practical signal acquisition applications, including medical imaging and remote sensing, this assumption is violated as the projections must be taken in groups. In this paper, we consider such applications and derive requirements on the number of measurements needed for successful recovery of signals when groups of dependent projections are taken at random. We find a penalty factor on the number of required measurements with respect to the standard CS scheme that employs conventional independent measurement selection and evaluate the accuracy of the predicted penalty through simulations. [ABSTRACT FROM PUBLISHER]

The application of nonlinear transformations to a cyclostationary signal for the purpose of revealing hidden periodicities has proven to be useful for applications requiring signal selectivity and noise tolerance. The fact that the hidden periodicities, referred to as cyclic moments, are often compressible in the Fourier domain motivates the use of compressive sensing (CS) as an efficient acquisition protocol for capturing such signals. In this paper, we consider the class of Temporal Higher Order Cyclostationary Statistics (THOCS) estimators when CS is used to acquire the cyclostationary signal assuming compressible cyclic moments in the Fourier domain. We develop a theoretical framework for estimating THOCS using the low-rate nonuniform sampling protocol from CS and illustrate the performance of this framework using simulated data. [ABSTRACT FROM PUBLISHER]

We investigate the problem of enumerating source signals impinging on an array of sensors given noisy, limited observations. The assumption of a large sample size is indispensable for most of the existing approaches so that they suffer significant performance degradation when only a small number of samples is available. Random matrix theory can capture the asymptotic distributions of the eigenvalues accurately and provide good approximations even for a finite sample size. In this paper, we take into account the relationship and distributions of the noise and signal eigenvalues based on random matrix theory and derive a simple two-step test. Numerical simulations demonstrate that it is capable of correctly determining the number of sources in the case of small sample sizes. [ABSTRACT FROM PUBLISHER]

This paper presents the results of a comprehensive study of the shingled writing process and various signal processing and data detection approaches applied to the readback waveforms. The recording simulations include realistic head fields, a random granular media, magnetostatic and exchange interactions, and a READ head sensitivity function. Readback waveforms are examined in both one and two dimensions in terms of signal characteristics (linear and nonlinear), noise behavior (stationary and signal-dependent), and intertrack interference. Different equalization and detection approaches are compared and about a 10% density gain is reported for such 2-D magnetic recording compared with traditional single-track recording. These gains depend strongly on the number of readers, the reader positioning, and the reader width. [ABSTRACT FROM AUTHOR]

A new strain estimator for quasi-static elastography is presented, based on tracking of the analytical signal phase as a function of the external force. Two implementations are introduced: zero-phase search with moving window (SMW) and zero-phase band tracking using connected component labeling (CCL). Low analytical signal amplitude caused by local destructive interference is associated with large error in the phase trajectories, and amplitude thresholding can thus be used to terminate the phase tracking along a particular path. Interpolation is then applied to estimate displacement in the eliminated path. The paper describes first a mathematical analysis based on 1-D multi-scatter modeling, followed by a statistical study of the displacement and strain error. Simulation and experiment with an inhomogeneous phantom indicate that SMW and CCL are capable of reliably estimating tissue displacement and strain over a larger range of deformation than standard timedomain cross-correlation (SCC). Results also show that SMW is roughly 40 times faster than SCC with comparable or even better accuracy. CCL is slower than SMW, but more noise robust. Simulation assessment at compression level 3% and 6% with SNR 20 dB demonstrates average strain error for SMW and CCL of 10%, whereas SCC achieves 18%. [ABSTRACT FROM AUTHOR]

This paper investigates the in-line differential push-pull signal simulation for the Blu-ray disk system using the scalar diffraction theory. A simple calculation scheme was proposed. With the simulation flow, six different types of in-line gratings were analyzed, compared, and discussed. The simulation results show that the pattern with three segmented central regions has the best signal performance. [ABSTRACT FROM PUBLISHER]