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# IEEE Transactions on Signal Processing

## Filter Results

Displaying Results 1 - 25 of 41

Publication Year: 2008, Page(s):C1 - C4
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• ### IEEE Transactions on Signal Processing publication information

Publication Year: 2008, Page(s): C2
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• ### Spatially Adaptive Estimation via Fitted Local Likelihood Techniques

Publication Year: 2008, Page(s):873 - 886
Cited by:  Papers (9)
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This paper offers a new technique for spatially adaptive estimation. The local likelihood is exploited for nonparametric modeling of observations and estimated signals. The approach is based on the assumption of a local homogeneity of the signal: for every point there exists a neighborhood in which the signal can be well approximated by a constant. The fitted local likelihood statistics are used f... View full abstract»

• ### Robust Nuclear Quadrupole Resonance Signal Detection Allowing for Amplitude Uncertainties

Publication Year: 2008, Page(s):887 - 894
Cited by:  Papers (10)  |  Patents (3)
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Nuclear quadrupole resonance (NQR) is a solid-state radio frequency spectroscopic technique that can be used to detect compounds which contain quadrupolar nuclei, a requirement fulfilled by many high explosives and narcotics. Unfortunately, the low signal-to-noise ratio (SNR) of the observed signals currently inhibits the widespread use of the technique, thus highlighting the need for intelligent ... View full abstract»

• ### Maximum-Likelihood Estimation, the CramÉr–Rao Bound, and the Method of Scoring With Parameter Constraints

Publication Year: 2008, Page(s):895 - 908
Cited by:  Papers (16)
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Maximum-likelihood (ML) estimation is a popular approach to solving many signal processing problems. Many of these problems cannot be solved analytically and so numerical techniques such as the method of scoring are applied. However, in many scenarios, it is desirable to modify the ML problem with the inclusion of additional side information. Often this side information is in the form of parametri... View full abstract»

• ### Covariance Matrix Estimation With Heterogeneous Samples

Publication Year: 2008, Page(s):909 - 920
Cited by:  Papers (27)
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We consider the problem of estimating the covariance matrix Mp of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly Mp. More precisely, we assume that the training samples can be clustered into K groups, each one containing Lk, snapshots sharing the same covariance matrix Mk. Furthermore,... View full abstract»

• ### An EM Algorithm for Nonlinear State Estimation With Model Uncertainties

Publication Year: 2008, Page(s):921 - 936
Cited by:  Papers (35)
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In most solutions to state estimation problems, e.g., target tracking, it is generally assumed that the state transition and measurement models are known a priori. However, there are situations where the model parameters or the model structure itself are not known a priori or are known only partially. In these scenarios, standard estimation algorithms like the Kalman filter and the extended Kalman... View full abstract»

• ### Sequential Monte Carlo Methods for Tracking Multiple Targets With Deterministic and Stochastic Constraints

Publication Year: 2008, Page(s):937 - 948
Cited by:  Papers (26)
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In multitarget scenarios, kinematic constraints from the interaction of targets with their environment or other targets can restrict target motion. Such motion constraint information could improve tracking performance if effectively used by the tracker. In this paper, we propose three particle filtering methods that incorporate constraint information in their proposal and weighting process; the nu... View full abstract»

• ### Signal Modeling and Classification Using a Robust Latent Space Model Based on $t$ Distributions

Publication Year: 2008, Page(s):949 - 963
Cited by:  Papers (28)
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Factor analysis is a statistical covariance modeling technique based on the assumption of normally distributed data. A mixture of factor analyzers can be hence viewed as a special case of Gaussian (normal) mixture models providing a mathematically sound framework for attribute space dimensionality reduction. A significant shortcoming of mixtures of factor analyzers is the vulnerability of normal d... View full abstract»

• ### Asymptotically Efficient Reduced Complexity Frequency Offset and Channel Estimators for Uplink MIMO-OFDMA Systems

Publication Year: 2008, Page(s):964 - 979
Cited by:  Papers (20)
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In this paper, we address the joint data-aided estimation of frequency offsets and channel coefficients in uplink multiple-input multiple-output orthogonal frequency-division multiple access (MIMO-OFDMA) systems. As the maximum-likelihood (ML) estimator is impractical in this context, we introduce a family of suboptimal estimators with the aim of exhibiting an attractive tradeoff between performan... View full abstract»

• ### Algebraic Joint Zero-Diagonalization and Blind Sources Separation

Publication Year: 2008, Page(s):980 - 989
Cited by:  Papers (13)
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This paper adresses the problem of the joint zero-diagonalization of a given set of matrices. We establish the identiflability conditions of the zero-diagonalizer, and we propose a new algebraical algorithm based on the reformulation of the initial problem into a joint-diagonalization problem. The zero-diagonalizer is not constrained to be unitary. Computer simulations illustrate the behavior of t... View full abstract»

• ### Performance Analysis of GPS Receivers in Non-Gaussian Noise Incorporating Precorrelation Filter and Sampling Rate

Publication Year: 2008, Page(s):990 - 1004
Cited by:  Papers (18)
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Global positioning system (GPS) receivers find growing applications in indoor and outdoor communication environments, including urban and rural areas. Interference and noise sources for GPS receivers may assume Gaussian or non-Gaussian distributions. The GPS receiver performance under Gaussian additive noise has been studied. Non-Gaussian noise may equally contaminate the GPS satellite signals and... View full abstract»

• ### Relationship Between Geometric Translations and TLS Estimation Bias in Bearings-Only Target Localization

Publication Year: 2008, Page(s):1005 - 1017
Cited by:  Papers (14)
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This paper analyzes the effects of local coordinate translations and rotations on the bias and mean-squared error performance of the total least squares (TLS) bearings-only target localization algorithm. The TLS estimator was originally proposed to alleviate the severe bias problems associated with the traditional pseudolinear estimator. An interesting property of the TLS estimator, which is not s... View full abstract»

• ### Stochastic Analysis of the LMS Algorithm for System Identification With Subspace Inputs

Publication Year: 2008, Page(s):1018 - 1027
Cited by:  Papers (8)
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This paper studies the behavior of the low-rank least mean squares (LMS) adaptive algorithm for the general case in which the input transformation may not capture the exact input subspace. It is shown that the Independence Theory and the independent additive noise model are not applicable to this case. A new theoretical model for the weight mean and fluctuation behaviors is developed which incorpo... View full abstract»

• ### Multiaccess Interference Suppression in Orthogonal Space–Time Block Coded MIMO Systems by Adaptive Projected Subgradient Method

Publication Year: 2008, Page(s):1028 - 1042
Cited by:  Papers (21)
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This paper introduces adaptive filters that are effective to suppress multiple access interference (MAI) in orthogonal space-time block coded/ multiple-input multiple-output (OSTBC-MIMO) systems. We define an optimal linear filter that minimizes the mean-square error between the filter output and a scaled version of the desired output under a constraint defined by the available channel state infor... View full abstract»

• ### Determination of the Number of Errors in DFT Codes Subject to Low-Level Quantization Noise

Publication Year: 2008, Page(s):1043 - 1054
Cited by:  Papers (12)
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This paper analyzes the effects of quantization or other low-level noise on the error correcting capability of a popular class of real-number Bose-Chaudhuri-Hocquenghem (BCH) codes known as discrete Fourier transform (DFT) codes. In the absence of low-level noise, a modified version of the Peterson-Gorenstein-Zierler (PGZ) algorithm allows the correction of up to corrupted entries in the real-valu... View full abstract»

• ### Nonideal Sampling and Regularization Theory

Publication Year: 2008, Page(s):1055 - 1070
Cited by:  Papers (19)  |  Patents (4)
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Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, which may or may not be bandlimited. In this paper, we present some further justification for this type of representation, while addressing the issue of the specification of the best reconstruction space. We consider a realistic setting ... View full abstract»

• ### Causal Compensation for Erasures in Frame Representations

Publication Year: 2008, Page(s):1071 - 1082
Cited by:  Papers (4)
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In a variety of signal processing and communications contexts, erasures occur inadvertently or can be intentionally introduced as part of a data reduction strategy. This paper discusses causal compensation for erasures in frame representations of signals. The approach described assumes linear synthesis of the signal using a prespecified frame but no specific generation mechanism for the coefficien... View full abstract»

• ### Cooperative Learning Algorithms for Data Fusion Using Novel $L_{1}$ Estimation

Publication Year: 2008, Page(s):1083 - 1095
Cited by:  Papers (14)
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Two novel L1 estimation methods for multisensor data fusion are developed, respectively in the case of known and unknown scaling coefficients. Two discrete-time cooperative learning (CL) algorithms are proposed to implement the two proposed methods. Compared with the high-order statistical method and the entropy estimation method, the two proposed estimation methods can minimize a conve... View full abstract»

• ### Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization

Publication Year: 2008, Page(s):1096 - 1105
Cited by:  Papers (103)
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In this paper, we study simultaneous matrix diagonalization-based techniques for the estimation of the mixing matrix in underdetermined independent component analysis (ICA). This includes a generalization to underdetermined mixtures of the well-known SOBI algorithm. The problem is reformulated in terms of the parallel factor decomposition (PARAFAC) of a higher-order tensor. We present conditions u... View full abstract»

• ### Signal Interpretation of Multifunction Radars: Modeling and Statistical Signal Processing With Stochastic Context Free Grammar

Publication Year: 2008, Page(s):1106 - 1119
Cited by:  Papers (13)
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Multifunction radars (MFRs) are sophisticated sensors with complex dynamical modes that are widely used in surveillance and tracking. Because of their agility, a new solution to the interpretation of radar signal is critical to aircraft survivability and successful mission completion. The MFRs' three main characteristics that make their signal interpretation challenging are: i) MFRs' behavior is m... View full abstract»

• ### Adaptive Polarized Waveform Design for Target Tracking Based on Sequential Bayesian Inference

Publication Year: 2008, Page(s):1120 - 1133
Cited by:  Papers (43)
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In this paper, we develop an adaptive waveform design method for target tracking under a framework of sequential Bayesian inference. We employ polarization diversity to improve the tracking accuracy of a target in the presence of clutter. We use an array of electromagnetic (EM) vector sensors to fully exploit the polarization information of the reflected signal. We apply a sequential Monte Carlo m... View full abstract»

• ### Steepest Descent Algorithms for Optimization Under Unitary Matrix Constraint

Publication Year: 2008, Page(s):1134 - 1147
Cited by:  Papers (52)
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In many engineering applications we deal with constrained optimization problems with respect to complex-valued matrices. This paper proposes a Riemannian geometry approach for optimization of a real-valued cost function T of complex-valued matrix argument W, under the constraint that W is an n times n unitary matrix. We derive steepest descent (SD) algorithms on the Lie group of unitary matrices U... View full abstract»

• ### Design and Analysis of MMSE Pilot-Aided Cyclic-Prefixed Block Transmissions for Doubly Selective Channels

Publication Year: 2008, Page(s):1148 - 1160
Cited by:  Papers (45)  |  Patents (5)
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This paper considers affine cyclic-prefixed block-based pilot-aided transmission (PAT) over the single-antenna doubly selective channel, where the channel is assumed to obey a complex-exponential basis expansion model. First, a tight lower bound on the mean-squared error (MSE) of pilot-aided channel estimates is derived, along with necessary and sufficient conditions on the pilot/data pattern that... View full abstract»

• ### A Low-Complexity PTS-Based Radix FFT Method for PAPR Reduction in OFDM Systems

Publication Year: 2008, Page(s):1161 - 1166
Cited by:  Papers (25)
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A low-complexity partial transmit sequence (PTS) technique for reducing the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) signal is presented. Signals at the middle stages of an -point radix FFT using decimation in frequency (DIF) or decimation in time (DIT) are considered for PTS subblocking. We show that DIF has a lower multiplicative complexity than ... 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