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# IEEE Transactions on Signal Processing

## Filter Results

Displaying Results 1 - 20 of 20
• ### Editorial A Brief Message From the New Editor-in-Chief

Publication Year: 2018, Page(s): 1952
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• ### Noise Enhancement in Robust Estimation of Location

Publication Year: 2018, Page(s):1953 - 1966
| | PDF (839 KB)

In this paper, we investigate the noise benefits to maximum likelihood type estimators (M-estimator) for the robust estimation of a location parameter. Two distinct noise benefits are shown to be accessible under these conditions. With symmetric heavy-tailed noise distributions, the asymptotic efficiency of the estimation can be enhanced by injecting extra noise into the M-estimators. With an asym... View full abstract»

• ### Large-Scale Kernel-Based Feature Extraction via Low-Rank Subspace Tracking on a Budget

Publication Year: 2018, Page(s):1967 - 1981
| | PDF (2008 KB) | HTML

Kernel-based methods enjoy powerful generalization capabilities in learning a variety of pattern recognition tasks. When such methods are provided with sufficient training data, broadly applicable classes of nonlinear functions can be approximated with desired accuracy. Nevertheless, inherent to the nonparametric nature of kernel-based estimators are computational and memory requi... View full abstract»

• ### Optimal Bayesian Kalman Filtering With Prior Update

Publication Year: 2018, Page(s):1982 - 1996
| | PDF (1877 KB)

In many practical filter design problems, the exact statistical information of the underlying random processes is not available. One robust filtering approach in these situations is to design an intrinsically Bayesian robust filter that provides optimal solution relative to the prior distribution governing the uncertainty class of all possible joint random process models. In this context, the intr... View full abstract»

• ### Subspace Rejection for Matching Pursuit in the Presence of Unresolved Targets

Publication Year: 2018, Page(s):1997 - 2010
| | PDF (1178 KB)

Unresolved scatterers (separated by less than a 3-dB matched filter main lobe width) are known to degrade the matching pursuit performances in radar: It tends to generate spurious detection or miss weaker targets, hidden in strong sidelobes. In this paper, we propose a new matching pursuit algorithm performing a subspace radar resolution cell rejection. The philosophy is the following: As it is us... View full abstract»

Publication Year: 2018, Page(s):2011 - 2026
| | PDF (1606 KB) | HTML

This paper investigates the relay hybrid precoding design in millimeter-wave massive multiple-input multiple-output systems. The optimal design of the relay hybrid precoding is highly nonconvex, due to the six-order polynomial objective function, six-order polynomial constraint, and constant-modulus constraints. To efficiently solve this challenging nonconvex problem, we first reformulate it into ... View full abstract»

• ### Asymmetric Pulse Modeling for FRI Sampling

Publication Year: 2018, Page(s):2027 - 2040
| | PDF (1763 KB) | HTML Media

We consider sampling and reconstruction of finite-rate-of-innovation (FRI) signals such as a train of pulses, where the pulses have varying degrees of asymmetry. We address the problem of asymmetry modeling starting from a given symmetric prototype. We show that among the class of unitary operators that are linear and invariant to translation and scale, the fractional Hilbert (FrH) operator is View full abstract»

• ### Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation

Publication Year: 2018, Page(s):2041 - 2054
| | PDF (1539 KB) | HTML Media

We consider the blind source separation (BSS) problem and the closely related approximate joint diagonalization (AJD) problem of symmetric positive definite (SPD) matrices. These two problems can be reduced to an optimization problem with three key components: the criterion to minimize, the constraint on the solution, and the optimization algorithm to solve it. This paper contains two contribution... View full abstract»

Publication Year: 2018, Page(s):2055 - 2069
| | PDF (1958 KB) | HTML

From the attenuation measurements collected by a network of spatially distributed sensors, radio tomography constructs spatial loss fields (SLFs) that quantify absorption of radiofrequency waves at each location. These SLFs can be used for interference prediction in (possibly cognitive) wireless communication networks, for environmental monitoring or intrusion detection in surveillance application... View full abstract»

• ### Attack Detection in Sensor Network Target Localization Systems With Quantized Data

Publication Year: 2018, Page(s):2070 - 2085
| | PDF (1092 KB) | HTML

We consider a sensor network focused on target localization, where sensors measure the signal strength emitted from the target. Each measurement is quantized to one bit and sent to the fusion center. A general attack is considered at some sensors that attempts to cause the fusion center to produce an inaccurate estimation of the target location. The attack is a combination of man-in-the-middle, ha... View full abstract»

• ### Uniform Recovery Bounds for Structured Random Matrices in Corrupted Compressed Sensing

Publication Year: 2018, Page(s):2086 - 2097
| | PDF (523 KB) | HTML

We study the problem of recovering an $s$ -sparse signal $mathbf{x}^{star }in mathbb {C}^n$ from corrupted measurements $mathbf{y}=mathbf{A}mathbf{x}^{star }+mathbf{z}^{star }+mathbf{w}$ View full abstract»

• ### Optimized Update/Prediction Assignment for Lifting Transforms on Graphs

Publication Year: 2018, Page(s):2098 - 2111
| | PDF (3103 KB) | HTML Media

Transformations on graphs can provide compact representations of signals with many applications in denoising, feature extraction, or compression. In particular, lifting transforms have the advantage of being critically sampled and invertible by construction, but the efficiency of the transform depends on the choice of a good bipartition of the graph into update ( View full abstract»

• ### Multiple Scan Data Association by Convex Variational Inference

Publication Year: 2018, Page(s):2112 - 2127
| | PDF (1606 KB) | HTML Media

Data association, the reasoning over correspondence between targets and measurements, is a problem of fundamental importance in target tracking. Recently, belief propagation (BP) has emerged as a promising method for estimating the marginal probabilities of measurement to target association, providing fast, accurate estimates. The excellent performance of BP in the particular formulation used may ... View full abstract»

• ### On the Use of Extrinsic Probabilities in the Computation of Non-Bayesian Cramér–Rao Bounds for Coded Linearly Modulated Signals

Publication Year: 2018, Page(s):2128 - 2140
| | PDF (1266 KB) | HTML

This contribution considers the non-Bayesian Cramér–Rao bound (CRB) related to parameter estimation from a linearly modulated signal observed in additive white Gaussian noise. We compare the exact CRB expression for coded modulation with two ad hoc CRB (ACRB) expressions; the first ACRB is obtained by substituting in the exact CRB expression for uncoded modulation th... View full abstract»

• ### ToPs: Ensemble Learning With Trees of Predictors

Publication Year: 2018, Page(s):2141 - 2152
| | PDF (1772 KB) | HTML Media

We present a new approach to ensemble learning. Our approach differs from previous approaches in that it constructs and applies different predictive models to different subsets of the feature space. It does this by constructing a tree of subsets of the feature space and associating a predictor (predictive model) to each node of the tree; we call the resulting object a tree of predictors View full abstract»

• ### Structure-Aware Bayesian Compressive Sensing for Frequency-Hopping Spectrum Estimation With Missing Observations

Publication Year: 2018, Page(s):2153 - 2166
| | PDF (1041 KB) | HTML

In this paper, we address the problem of spectrum estimation of multiple frequency-hopping (FH) signals in the presence of random missing observations. The signals are analyzed within the bilinear time–frequency (TF) representation framework, where a TF kernel is designed by exploiting the inherent FH signal structures. The designed kernel permits effective suppression of cross-terms and ar... View full abstract»

• ### A Robust Parallel Algorithm for Combinatorial Compressed Sensing

Publication Year: 2018, Page(s):2167 - 2177
| | PDF (1257 KB) | HTML

It was shown in previous work that a vector $mathbf{x} in mathbb {R}^n$ with at most $k < n$ nonzeros can be recovered from an expander sketch $mathbf{A}mathbf{x}$ in View full abstract»

• ### Asymptotic Confidence Regions for High-Dimensional Structured Sparsity

Publication Year: 2018, Page(s):2178 - 2190
| | PDF (1440 KB) | HTML

In the setting of high-dimensional linear regression models, we propose two frameworks for constructing pointwise and group confidence sets for penalized estimators, which incorporate prior knowledge about the organization of the nonzero coefficients. This is done by desparsifying the estimator by S. van de Geer and B. Stucky and S. van de Geer et al., then using an appropr... View full abstract»

• ### Navigation With Cellular CDMA Signals—Part I: Signal Modeling and Software-Defined Receiver Design

Publication Year: 2018, Page(s):2191 - 2203
| | PDF (5991 KB) | HTML

A software-defined receiver (SDR) for navigation using cellular code-division multiple access (CDMA) signals is presented. The cellular forward link signal structure is described, and models for the transmitted and received signals are developed. Particular attention is paid to relevant information that could be extracted and subsequently exploited for positioning and timing purposes. The pseudora... View full abstract»

• ### Navigation With Cellular CDMA Signals—Part II: Performance Analysis and Experimental Results

Publication Year: 2018, Page(s):2204 - 2218
| | PDF (4218 KB) | HTML

A framework for navigation using cellular code division multiple access (CDMA) signals is studied in this paper. Theoretical lower bounds on the navigation performance using pseudorange measurements drawn from the cellular CDMA base transceiver stations (BTSs) are derived. Moreover, the navigation performance for a mapper/navigator framework is studied in the presence of timing discrepancies betwe... 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