# IEEE Transactions on Signal Processing

## Filter Results

Displaying Results 1 - 25 of 33
• ### [Front cover]

Publication Year: 2013, Page(s): C1
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• ### IEEE Transactions on Signal Processing publication information

Publication Year: 2013, Page(s): C2
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Publication Year: 2013, Page(s):219 - 220
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Publication Year: 2013, Page(s):221 - 222
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• ### Gaussian Process Regression for Sensor Networks Under Localization Uncertainty

Publication Year: 2013, Page(s):223 - 237
Cited by:  Papers (20)
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In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statist... View full abstract»

• ### The Sign-Definiteness Lemma and Its Applications to Robust Transceiver Optimization for Multiuser MIMO Systems

Publication Year: 2013, Page(s):238 - 252
Cited by:  Papers (9)
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We formally generalize the sign-definiteness lemma to the case of complex-valued matrices and multiple norm-bounded uncertainties. This lemma has found many applications in the study of the stability of control systems, and in the design and optimization of robust transceivers in communications. We then present three different novel applications of this lemma in the area of multi-user multiple-inp... View full abstract»

• ### An Adaptive Conditional Zero-Forcing Decoder With Full-Diversity, Least Complexity and Essentially-ML Performance for STBCs

Publication Year: 2013, Page(s):253 - 263
Cited by:  Papers (6)
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A low complexity, essentially-ML decoding technique for the Golden code and the three antenna Perfect code was introduced by Sirianunpiboon, Howard and Calderbank. Though no theoretical analysis of the decoder was given, the simulations showed that this decoding technique has almost maximum-likelihood (ML) performance. Inspired by this technique, in this paper we introduce two new low complexity d... View full abstract»

• ### Particle Based Smoothed Marginal MAP Estimation for General State Space Models

Publication Year: 2013, Page(s):264 - 273
Cited by:  Papers (2)
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We consider the smoothing problem for a general state space system using sequential Monte Carlo (SMC) methods. The marginal smoother is assumed to be available in the form of weighted random particles from the SMC output. New algorithms are developed to extract the smoothed marginal maximum a posteriori (MAP) estimate of the state from the existing marginal particle smoother. Our method does not n... View full abstract»

• ### Characterization of Non-Stationary Channels Using Mismatched Wiener Filtering

Publication Year: 2013, Page(s):274 - 288
Cited by:  Papers (12)
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A common simplification in the statistical treatment of linear time-varying (LTV) wireless channels is the approximation of the channel as a stationary random process inside certain time-frequency regions. We develop a methodology for the determination of local quasi-stationarity (LQS) regions, i.e., local regions in which a channel can be treated as stationary. Contrary to previous results relyin... View full abstract»

• ### A Semi-Parallel Successive-Cancellation Decoder for Polar Codes

Publication Year: 2013, Page(s):289 - 299
Cited by:  Papers (88)  |  Patents (3)
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Polar codes are a recently discovered family of capacity-achieving codes that are seen as a major breakthrough in coding theory. Motivated by the recent rapid progress in the theory of polar codes, we propose a semi-parallel architecture for the implementation of successive cancellation decoding. We take advantage of the recursive structure of polar codes to make efficient use of processing resour... View full abstract»

• ### Channel-Aware Decentralized Detection via Level-Triggered Sampling

Publication Year: 2013, Page(s):300 - 315
Cited by:  Papers (17)
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We consider decentralized detection through distributed sensors that perform level-triggered sampling and communicate with a fusion center (FC) via noisy channels. Each sensor computes its local log-likelihood ratio (LLR), samples it using the level-triggered sampling mechanism, and at each sampling instant transmits a single bit to the FC. Upon receiving a bit from a sensor, the FC updates the gl... View full abstract»

• ### $H_{infty}$ Fixed-Interval Smoothing Estimation for Time-Delay Systems

Publication Year: 2013, Page(s):316 - 326
Cited by:  Papers (2)
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This paper is concerned with the H∞ fixed-interval smoothing estimation for time-delay systems which include continuous-time case and discrete-time case. In the case of discrete-time systems, the problem can be solved by using the conventional state augmentation approach. However, this approach is not suitable for the continuous-time case. In this paper, we will propose a ... View full abstract»

• ### Quantization and Bit Allocation for Channel State Feedback in Relay-Assisted Wireless Networks

Publication Year: 2013, Page(s):327 - 339
Cited by:  Papers (3)
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This paper investigates quantization of channel state information (CSI) and bit allocation across wireless links in a multi-source, single-relay cooperative cellular network. Our goal is to minimize the loss in performance, measured as the achievable sum rate, due to limited-rate quantization of CSI. We develop both a channel quantization scheme and allocation of limited feedback bits to the vario... View full abstract»

• ### Efficient High-Dimensional Inference in the Multiple Measurement Vector Problem

Publication Year: 2013, Page(s):340 - 354
Cited by:  Papers (32)
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In this work, a Bayesian approximate message passing algorithm is proposed for solving the multiple measurement vector (MMV) problem in compressive sensing, in which a collection of sparse signal vectors that share a common support are recovered from undersampled noisy measurements. The algorithm, AMP-MMV, is capable of exploiting temporal correlations in the amplitudes of non-zero coefficients, a... View full abstract»

• ### Joint Probability Mass Function Estimation From Asynchronous Samples

Publication Year: 2013, Page(s):355 - 364
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A common approach to study the relationship between different signals is to model them as random processes and estimate their joint probability distribution from the observed data. When synchronous samples of the random processes are available, then the empirical distribution gives a reliable estimate. However, in several situations, such as sensors spread over a vast region or a software probing ... View full abstract»

• ### Cramér-Rao Bound for Circular and Noncircular Complex Independent Component Analysis

Publication Year: 2013, Page(s):365 - 379
Cited by:  Papers (15)
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Despite an increased interest in complex independent component analysis (ICA) during the last two decades, a closed form expression for the Cramér-Rao bound (CRB) for the demixing matrix is not known yet. In this paper, we fill this gap by deriving a closed-form expression for the CRB of the demixing matrix for instantaneous noncircular complex ICA. It contains the CRB for circular complex... View full abstract»

• ### On the Selection of Optimum Savitzky-Golay Filters

Publication Year: 2013, Page(s):380 - 391
Cited by:  Papers (30)
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Savitzky-Golay (S-G) filters are finite impulse response lowpass filters obtained while smoothing data using a local least-squares (LS) polynomial approximation. Savitzky and Golay proved in their hallmark paper that local LS fitting of polynomials and their evaluation at the mid-point of the approximation interval is equivalent to filtering with a fixed impulse response. The problem that we addre... View full abstract»

• ### Visual Tracking in Background Subtracted Image Sequences via Multi-Bernoulli Filtering

Publication Year: 2013, Page(s):392 - 397
Cited by:  Papers (47)
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This correspondence presents a novel method for simultaneous tracking of multiple non-stationary targets in video. Our method operates directly on the video data and does not require any detection. We propose a multi-target likelihood function for the background-subtracted grey-scale image data, which admits multi-target conjugate priors. This allows the multi-target posterior to be efficiently pr... View full abstract»

• ### Perturbation Analysis of Orthogonal Matching Pursuit

Publication Year: 2013, Page(s):398 - 410
Cited by:  Papers (24)
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Orthogonal Matching Pursuit (OMP) is a canonical greedy pursuit algorithm for sparse approximation. Previous studies of OMP have considered the recovery of a sparse signal through Φ and y = Φx + b, where is a matrix with more columns than rows and denotes the measurement noise. In this paper, based on Restricted Isometry Property (RIP), the performance of OMP is analyzed under genera... View full abstract»

• ### Load Balanced Resampling for Real-Time Particle Filtering on Graphics Processing Units

Publication Year: 2013, Page(s):411 - 419
Cited by:  Papers (10)
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The application of particle filters to real-time systems is often limited because of their computational complexity, and hence the use of graphics processing units (GPUs) that contain hundreds of processing elements on a chip is very promising. However, parallel implementations of particle filters with state-of-the-art systematic resampling on a GPU suffer from a severe workload imbalance problem,... View full abstract»

• ### Stable Signal Reconstruction via $ell^1$-Minimization in Redundant, Non-Tight Frames

Publication Year: 2013, Page(s):420 - 426
Cited by:  Papers (10)
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In many signal and image processing applications, a desired clean signal is distorted from blur and noise. Reconstructing the clean signal usually yields to a high dimensional ill-conditioned system of equations, where a direct solution would severely amplify the noise. Stable signal reconstruction requires the use of regularization techniques, which incorporate a priori knowledge about the signal... View full abstract»

• ### Compressed Sensing With Prior Information: Information-Theoretic Limits and Practical Decoders

Publication Year: 2013, Page(s):427 - 439
Cited by:  Papers (28)
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This paper considers the problem of sparse signal recovery when the decoder has prior information on the sparsity pattern of the data. The data vector x=[x1,...,xN]T has a randomly generated sparsity pattern, where the i-th entry is non-zero with probability pi. Given knowledge of these probabilities, the decoder attempts to recover x bas... View full abstract»

• ### Estimation of NAND Flash Memory Threshold Voltage Distribution for Optimum Soft-Decision Error Correction

Publication Year: 2013, Page(s):440 - 449
Cited by:  Papers (32)  |  Patents (1)
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As the feature size of NAND flash memory decreases, the threshold voltage signal becomes less reliable, and its distribution varies significantly with the number of program-erase (PE) cycles and the data retention time. We have developed parameter estimation algorithms to find the means and variances of the threshold voltage distribution that is modeled as a Gaussian mixture. The proposed methods ... View full abstract»

• ### D-MAP: Distributed Maximum a Posteriori Probability Estimation of Dynamic Systems

Publication Year: 2013, Page(s):450 - 466
Cited by:  Papers (31)
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This paper develops a framework for the estimation of a time-varying random signal using a distributed sensor network. Given a continuous time model sensors collect noisy observations and produce local estimates according to the discrete time equivalent system defined by the sampling period of observations. Estimation is performed using a maximum a posteriori probability estimator (MAP) within a g... View full abstract»

• ### Optimization of Cooperative Beamforming for SC-FDMA Multi-User Multi-Relay Networks by Tractable D.C. Programming

Publication Year: 2013, Page(s):467 - 479
Cited by:  Papers (19)
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This paper addresses the optimal cooperative beamforming design for multi-user multi-relay wireless networks in which the single-carrier frequency division multiple access (SC-FDMA) technique is employed at the terminals. The problem of interest is to find the beamforming weights across relays to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among source users subject to indi... View full abstract»

## Aims & Scope

IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Pier Luigi Dragotti
Imperial College London