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This page shows you the most recent publications within this specialty of the MedWorm directory. This is page number 3.

Commutative Anisotropic Convolution on the 2-Sphere
We develop a new type of convolution between two signals on the 2-sphere. This is the first type of convolution on the 2-sphere which is commutative. Two other advantages, in comparison with existing definitions in the literature, are that 1) the new convolution admits anisotropic filters and signals and 2) the domain of the output remains on the sphere. Therefore, the new convolution well emulates the conventional Euclidean convolution. In addition to providing the new definition of convolution and discussing its properties, we provide the spectral analysis of the convolution output. This convolutional framework can be us...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

A Fast Design Method for Perfect-Reconstruction Uniform Cosine-Modulated Filter Banks
In this correspondence, we present a new and fast design algorithm for perfect-reconstruction (PR), maximally decimated, uniform, cosine-modulated filter banks. Perfect reconstruction is obtained within arithmetic machine precision. The new design does not need numerical optimization routines and is significantly faster than a competing method based on second-order cone programming (SOCP). The proposed design algorithm finds the optimum solution by iteratively solving a quadratic programming problem with linear equality constraints. By a special modification of the basic algorithm, we obtain PR filter banks with high stopb...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Reduced-Complexity Constrained Recursive Least-Squares Adaptive Filtering Algorithm
A linearly-constrained recursive least-squares adaptive filtering algorithm based on the method of weighting and the dichotomous coordinate descent (DCD) iterations is proposed. The method of weighting is employed to incorporate the linear constraints into the least-squares problem. The normal equations of the resultant unconstrained least-squares problem are then solved using the DCD iterations. The proposed algorithm has a significantly smaller computational complexity than the previously proposed constrained recursive least square (CRLS) algorithm while delivering convergence performance on par with CRLS. The effectiven...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Steady-State Solution of the Deficient Length Constrained FBLMS Algorithm
In almost all analyses of the frequency-domain block least mean-square (FBLMS) algorithm, the length of the adaptive filter is assumed to be equal to that of the unknown system impulse response. However, in many practical situations, where the length of the system impulse response is extremely long, the adaptive filter usually works in an under-modeling situation. The analysis results for the sufficient length FBLMS algorithm are not applicable to the deficient length case. In this correspondence, the steady-state solution of the deficient length constrained FBLMS algorithm is analyzed. Simulations illustrate the accuracy ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Computationally Efficient Capon- and APES-Based Coherence Spectrum Estimation
The coherence spectrum is of notable interest as a bivariate spectral measure in a variety of application, and the topic has lately attracted interest with the recent formulation of several high-resolution data adaptive estimators. In this work, we further this development with the presentation of computationally efficient implementations of the Capon- and APES-based MSC estimators. The presented implementations furthers the recent development of exploiting the estimators' inherently low displacement rank of the necessary products of Toeplitz-like matrices to include also the required cross-correlation covariance matrices ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Extensions to the Theory of Widely Linear Complex Kalman Filtering
For an improper complex signal ${bf x}$, its complementary covariance $E{bf x}{bf x}^T$ is not zero and thus it carries useful statistical information about ${bf x}$. Widely linear processing exploits Hermitian and complementary covariance to improve performance. In this paper, we extend the existing theory of widely linear complex Kalman filters (WLCKF) and unscented WLCKFs [D. P. Mandic and S. L. Goh,Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models (New York: Wiley, 2009)]. We propose a WLCKF which can deal with more general dynamical models of complex-valued states and measureme...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Instantaneous Relaying: Optimal Strategies and Interference Neutralization
In a multi-user wireless network equipped with multiple relay nodes, some relays are more intelligent than other relay nodes. The intelligent relays are able to gather channel state information, perform linear processing and forward signals whereas the dumb relays are only able to serve as amplifiers. As the dumb relays are oblivious to the source and destination nodes, the wireless network can be modeled as a relay network with smart instantaneous relay only: the signals of the source-destination link arrive at the same time as the source-relay-destination link. Recently, instantaneous relaying is shown to improve the deg...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Beamforming in Non-Regenerative MIMO Broadcast Relay Networks
This paper studies a multiple-input multiple-output (MIMO) broadcast relay channel (BRC), in which a multiple-antenna base station (BS) communicates with multiple-antenna users through an infrastructure-based multiple-antenna relay station (RS). Applying dirty paper coding (DPC) at the BS and linear processing at the RS, our aim is to find the input covariance matrices and the RS beamforming matrix that maximize the system sum-rate. To solve this non-convex problem, a more tractable dual multiple access relay channel (MARC) is investigated and an alternating-minimization algorithm is proposed. Furthermore, the mapping from...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Feedback Allocation for OFDMA Systems With Slow Frequency-Domain Scheduling
We study the problem of allocating limited feedback resources across multiple users in an orthogonal-frequency-division-multiple-access downlink system with slow frequency-domain scheduling. Many flavors of slow frequency-domain scheduling (e.g., persistent scheduling, semi-persistent scheduling), that adapt user-sub-band assignments on a slower time-scale, are being considered in standards such as 3GPP Long-Term Evolution. In this paper, we develop a feedback allocation algorithm that operates in conjunction with any arbitrary slow frequency-domain scheduler with the goal of improving the throughput of the system. Given a...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Source Localization Using Sparse Large Aperture Arrays
In this paper, a novel source/target localization approach is proposed using a number of sensors (surrounding or not surrounding one or more sources) to form a sparse large aperture array of known geometry. Under a large array aperture, the array response (manifold vector) obeys a spherical wave rather than a plane wave propagation model. By rotating the array reference point to be at each of the array sensors, a number of covariance matrices are constructed. It is shown that the eigenvalues of these covariance matrices are related to the source location with respect to the array reference point. The proposed approach is r...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Average-Consensus in a Deterministic Framework— Part II: Central Connectivity
This paper considers the average-consensus problem within the same framework as the companion paper [K. Topley and V. Krishnamurthy, “Average-Consensus Algorithms in a Deterministic Framework—Part I: Strong Connectivity, IEEE Trans. Signal Process., vol. 60, no. 12, Dec. 2012]. Two distributed algorithms are proposed and shown to be analogous to the algorithms presented in the Part I of the paper with respect to the communication costs and conditions sufficient for average-consensus. We provide convergence proofs, as well as numerical examples that (i) illustrate the empirical convergence rate of all four alg...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Average-Consensus in a Deterministic Framework—Part I: Strong Connectivity
This paper considers the average-consensus problem in a network with arbitrary (but finite) communication delays. A novel Distributed-Averaging (DA) algorithm is presented and shown to achieve average-consensus if at any time $t$ there exists a finite time interval $[t, T_{t}]$ over which each node can communicate (via a time-respecting path) with all other nodes. For consensus variables with dimensions on the order of the network size, the DA algorithm requires an order of magnitude less data to be communicated and stored at each node as compared to an idealized algorithm that floods the initial data. In the companion pap...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Max-Min Optimal Joint Power Control and Distributed Beamforming for Two-Way Relay Networks Under Per-Node Power Constraints
This paper deals with optimal joint user power control and relay distributed beamforming for two-way relay networks, where two end-users exchange information through multiple relays, each of which is assumed to have its own power constraint. The problem includes the design of the distributed beamformer at the relays and the power control scheme for the two end-users to optimize the network performance. Considering the overall two-way network performance, we maximize the lower signal-to-noise ratio (SNR) of the two communication links. For single-relay networks, this maximization problem is solved analytically. For multi-re...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Feedback-Topology Designs for Interference Alignment in MIMO Interference Channels
Interference alignment (IA) is a joint-transmission technique for the interference channel that achieves the maximum degrees-of-freedom and provides linear scaling of the capacity with the number of users for high signal-to-noise ratios (SNRs). Most prior work on IA is based on the impractical assumption that perfect and global channel-state information (CSI) is available at all transmitters. However, to implement IA, each receiver has to feed back CSI to all interferers, resulting in overwhelming feedback overhead. In particular, the sum feedback rate of each receiver scales quadratically with the number of users even if ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Energy Spreading Transform Approach to Achieve Full Diversity and Full Rate for MIMO Systems
Full-diversity full-rate (FDFR) space-time codes achieve both high data rate and good reliability at the cost of high decoding complexity. In this paper, we propose a low-complexity MIMO scheme that achieves both full diversity and full rate over flat fading channels for a sufficiently large number of transmit and receive antennas. The proposed scheme is constructed by applying energy spreading transforms (EST's) to multiple data streams and spatially multiplexing the streams to multiple transmit antennas. Simulation results show that the proposed FDFR scheme outperforms the threaded algebraic space-time (TAST) code, which...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Joint Source and Relay Optimization for Two-Way Linear Non-Regenerative MIMO Relay Communications
In this paper, we investigate the challenging problem of joint source and relay optimization for two-way linear non-regenerative multiple-input multiple-output (MIMO) relay communication systems. We derive the optimal structure of the source and relay precoding matrices when linear minimal mean-squared error (MMSE) receivers are used at both destinations in the relay system. We show that for a broad class of frequently used objective functions for MIMO communications such as the MMSE, the maximal mutual information (MMI), and the minimax MSE, the optimal relay and source matrices have a general beamforming structure. This ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Transmitter-Receiver Designs for Highly Frequency Selective Channels in MIMO FBMC Systems
This paper studies the MIMO applicability to filter bank based multicarrier (FBMC) modulations for low coherence bandwidth channels. Under these conditions the channel frequency response cannot be modeled flat at a subcarrier level. This implies that the techniques originally devised for OFDM do not restore the orthogonality between subcarriers when they are directly applied to FBMC. Aiming at circumventing this problem we propose the design of two MIMO FBMC schemes, which are based on a new subband processing. The figures of merit that govern the design of the first and second scheme are the signal to leakage plus noise r...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Interference MIMO Relay Channel: Joint Power Control and Transceiver-Relay Beamforming
In this paper, we consider an interference multiple-input multiple-output (MIMO) relay system where multiple source nodes communicate with their desired destination nodes concurrently with the aid of distributed relay nodes all equipped with multiple antennas. We aim at minimizing the total source and relay transmit power such that a minimum signal-to-interference-plus-noise ratio (SINR) threshold is maintained at each receiver. An iterative joint power control and beamforming algorithm is developed to achieve this goal. The proposed algorithm exploits transmit-relay-receive beamforming technique to mitigate the interferen...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Distributed Optimal Beamformers for Cognitive Radios Robust to Channel Uncertainties
Through spatial multiplexing and diversity, multi-input multi-output (MIMO) cognitive radio (CR) networks can markedly increase transmission rates and reliability, while controlling the interference inflicted to peer nodes and primary users (PUs) via beamforming. The present paper optimizes the design of transmit- and receive-beamformers for ad hoc CR networks when CR-to-CR channels are known, but CR-to-PU channels cannot be estimated accurately. Capitalizing on a norm-bounded channel uncertainty model, the optimal beamforming design is formulated to minimize the overall mean-square error (MSE) from all data streams, while...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Grassmannian Differential Limited Feedback for Interference Alignment
Channel state information (CSI) in the interference channel can be used to reduce the dimension of received interference and helps achieve the channel's maximum multiplexing gain through what is known as interference alignment (IA). Most interference alignment algorithms require knowledge of all the interfering channels to compute the alignment precoders. CSI, considered available at the receivers, can be shared with the transmitters via limited feedback. When IA is done by coding over frequency extensions in a single antenna system, the required CSI lies on the Grassmannian manifold and its structure can be exploited in f...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Using Channel Output Feedback to Increase Throughput in Hybrid-ARQ
Hybrid automatic repeat request (ARQ) protocols have become common in many packet transmission systems due to their incorporation in various standards. Hybrid-ARQ combines the normal ARQ method with forward error correction (FEC) codes to increase reliability and throughput. In this paper, we look at improving upon this performance using feedback information from the destination, in particular, using a powerful FEC code in conjunction with a proposed linear feedback code for the Rayleigh block fading channels. The new hybrid-ARQ scheme is initially developed for full received packet feedback in a point-to-point link. It is...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Cluster-Based Differential Energy Detection for Spectrum Sensing in Multi-Carrier Systems
This paper presents a novel differential energy detection scheme for multi-carrier systems, which can form fast and reliable decision of spectrum availability even in very low signal-to-noise ratio (SNR) environment. For example, the proposed scheme can reach 90% in probability of detection (PD) and 10% in probability of false alarm (PFA) for the SNRs as low as $-{hbox{21 dB}}$, while the observation length is equivalent to 2 multi-carrier symbol duration. The underlying initiative of the proposed scheme is applying order statistics on the clustered differential energy-spectral-density (ESD) in order to exploit the channel...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Performance Analysis of Cognitive Spectrum-Sharing Single-Carrier Systems With Relay Selection
In this paper, we analyze the performance of cooperative spectrum sharing single-carrier (SC) relay systems. Taking into account the peak interference power at the primary user (PU) and the maximum transmit power at the secondary user (SU) network, two separate power allocation constraints are formed. For a two-hop decode-and-forward (DF) relaying protocol and two power allocation constraints, two relay selection schemes, namely, a full-channel state information (CSI)-based best relay selection (BRS) and a partial CSI-based best relay selection (PBRS), are proposed. The distributions of the end-to-end signal-to-noise ratio...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Approximating the LLR Distribution for a Class of Soft-Output MIMO Detectors
We present approximations of the LLR distribution for a class of fixed-complexity soft-output MIMO detectors, such as the optimal soft detector and the soft-output via partial marginalization detector. More specifically, in a MIMO AWGN setting, we approximate the LLR distribution conditioned on the transmitted signal and the channel matrix with a Gaussian mixture model (GMM). Our main results consist of an analytical expression of the GMM model (including the number of modes and their corresponding parameters) and a proof that, in the limit of high SNR, this LLR distribution converges in probability towards a unique Gaussian distribution.
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Quantization via Empirical Divergence Maximization
Empirical divergence maximization (EDM) refers to a recently proposed strategy for estimating $f$-divergences and likelihood ratio functions. This paper extends the idea to empirical vector quantization where one seeks to empirically derive quantization rules that maximize the Kullback-Leibler divergence between two statistical hypotheses. We analyze the estimator's error convergence rate leveraging Tsybakov's margin condition and show that rates as fast as $n^{-1}$ are possible, where $n$ equals the number of training samples. We also show that the Flynn and Gray algorithm can be used to efficiently compute EDM estimates ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Low-Complexity Blind Equalization for OFDM Systems With General Constellations
This paper proposes a low-complexity algorithm for blind equalization of data in orthogonal frequency division multiplexing (OFDM)-based wireless systems with general constellations. The proposed algorithm is able to recover the transmitted data even when the channel changes on a symbol-by-symbol basis, making it suitable for fast fading channels. The proposed algorithm does not require any statistical information about the channel and thus does not suffer from latency normally associated with blind methods. The paper demonstrates how to reduce the complexity of the algorithm, which becomes especially low at high signal-to...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

DOA Estimation Using a Greedy Block Coordinate Descent Algorithm
This paper presents a novel jointly sparse signal reconstruction algorithm for the DOA estimation problem, aiming to achieve faster convergence rate and better estimation accuracy compared to existing $ell _{2,1}$-norm minimization approaches. The proposed greedy block coordinate descent (GBCD) algorithm shares similarity with the standard block coordinate descent method for $ell _{2,1}$-norm minimization, but adopts a greedy block selection rule which gives preference to sparsity. Although greedy, the proposed algorithm is proved to also have global convergence in this paper. Through theoretical analysis we demonstrate it...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Finding Non-Overlapping Clusters for Generalized Inference Over Graphical Models
We present extensive numerical simulations that illustrate our block-graph framework with a variety of inference algorithms (e.g., those in the libDAI software package). These simulations show the improvements provided by our framework.
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Structure-Based Bayesian Sparse Reconstruction
Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical information (Gaussian or otherwise) to obtain near optimal estimates. In addition, we make use of the rich structure of the sensing matrix encountered in many signal processing applications to develop a fast sparse recovery algorithm. The computational complexity of the proposed algorithm is very low compared with the widely used convex relaxation methods as well as greedy matching pursu...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Simultaneous Codeword Optimization (SimCO) for Dictionary Update and Learning
We consider the data-driven dictionary learning problem. The goal is to seek an over-complete dictionary from which every training signal can be best approximated by a linear combination of only a few codewords. This task is often achieved by iteratively executing two operations: sparse coding and dictionary update. The focus of this paper is on the dictionary update step, where the dictionary is optimized with a given sparsity pattern. We propose a novel framework where an arbitrary set of codewords and the corresponding sparse coefficients are simultaneously updated, hence the term simultaneous codeword optimization (Sim...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

A Phase-Sensitive Approach to Filtering on the Sphere
This paper examines filtering on a sphere, by first examining the roles of spherical harmonic magnitude and phase. We show that phase is more important than magnitude in determining the structure of a spherical function. We examine the properties of linear phase shifts in the spherical harmonic domain, which suggest a mechanism for constructing finite-impulse-response (FIR) filters. We show that those filters have desirable properties, such as being associative, mapping spherical functions to spherical functions, allowing directional filtering, and being defined by relatively simple equations. We provide examples of the fi...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

A Multilevel Iterated-Shrinkage Approach to Penalized Least-Squares Minimization
The area of sparse approximation of signals is drawing tremendous attention in recent years. Typically, sparse solutions of underdetermined linear systems of equations are required. Such solutions are often achieved by minimizing an $l_{1}$ penalized least squares functional. Various iterative-shrinkage algorithms have recently been developed and are quite effective for handling these problems, often surpassing traditional optimization techniques. In this paper, we suggest a new iterative multilevel approach that reduces the computational cost of existing solvers for these inverse problems. Our method takes advantage of th...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Polynomial Smoothing of Time Series With Additive Step Discontinuities
This paper addresses the problem of estimating simultaneously a local polynomial signal and an approximately piecewise constant signal from a noisy additive mixture. The approach developed in this paper synthesizes the total variation filter and least-square polynomial signal smoothing into a unified problem formulation. The method is based on formulating an $ell_1$-norm regularized inverse problem. A computationally efficient algorithm, based on variable splitting and the alternating direction method of multipliers (ADMM), is presented. Algorithms are derived for both unconstrained and constrained formulations. The method...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

New Closed Formula for the Univariate Hermite Interpolating Polynomial of Total Degree and its Application in Medical Image Slice Interpolation
This work investigates the usefulness of univariate Hermite interpolation of the total degree (HTD) for a biomedical signal processing task: slice interpolation in a variety of medical imaging modalities. The HTD is an algebraically demanding interpolation method that utilizes information of the values of the signal to be interpolated at distinct support positions, as well as the values of its derivatives up to a maximum available order. First a novel closed form solution for the univariate Hermite interpolating polynomial is presented for the general case of arbitrarily spaced support points and its computational and alge...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Realization of 3-D Separable-Denominator Digital Filters With Low -Sensitivity
Three-dimensional (3-D) digital filters find applications in a variety of image and video signal processing problems. This paper presents a coefficient-sensitivity analysis for a wide class of 3-D digital filters with separable denominators in local state space that leads to an analytic formulation for sensitivity minimization, and to present two solution techniques for the sensitivity minimization problem at hand. To this end, a vector-matrix-vector decomposition of a given 3-D transfer function that separates the three variables and leads to a state-space realization in a form convenient for subsequent analysis. An $l_2$...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Message-Passing De-Quantization With Applications to Compressed Sensing
Estimation of a vector from quantized linear measurements is a common problem for which simple linear techniques are suboptimal—sometimes greatly so. This paper develops message-passing de-quantization (MPDQ) algorithms for minimum mean-squared error estimation of a random vector from quantized linear measurements, notably allowing the linear expansion to be overcomplete or undercomplete and the scalar quantization to be regular or non-regular. The algorithm is based on generalized approximate message passing (GAMP), a recently-developed Gaussian approximation of loopy belief propagation for estimation with linear t...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Exact Wavelets on the Ball
We develop an exact wavelet transform on the three-dimensional ball (i.e. on the solid sphere), which we name the flaglet transform. For this purpose we first construct an exact transform on the radial half-line using damped Laguerre polynomials and develop a corresponding quadrature rule. Combined with the spherical harmonic transform, this approach leads to a sampling theorem on the ball and a novel three-dimensional decomposition which we call the Fourier-Laguerre transform. We relate this new transform to the well-known Fourier-Bessel decomposition and show that band-limitedness in the Fourier-Laguerre basis is a suffi...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Fixed-Point Analysis and Parameter Selections of MSR-CORDIC With Applications to FFT Designs
Mixed-scaling-rotation (MSR) coordinate rotation digital computer (CORDIC) is an attractive approach to synthesizing complex rotators. This paper presents the fixed-point error analysis and parameter selections of MSR-CORDIC with applications to the fast Fourier transform (FFT). First, the fixed-point mean squared error of the MSR-CORDIC is analyzed by considering both the angle approximation error and signal round-off error incurred in the finite precision arithmetic. The signal to quantization noise ratio (SQNR) of the output of the FFT synthesized using MSR-CORDIC is thereafter estimated. Based on these analyses, two di...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Stochastic Analysis of a Stable Normalized Least Mean Fourth Algorithm for Adaptive Noise Canceling With a White Gaussian Reference
The least mean fourth (LMF) algorithm has several stability problems. Its stability depends on the variance and distribution type of the adaptive filter input, the noise variance, and the initialization of the filter weights. A global solution to these stability problems was presented recently for a normalized LMF (NLMF) algorithm. Here, a stochastic analysis of the mean-square deviation (MSD) of the globally stable NLMF algorithm is provided. The analysis is done in the context of adaptive noise canceling with a white Gaussian reference input and Gaussian, binary, and uniform desired signals. The analytical model is shown...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Diffusion Strategies Outperform Consensus Strategies for Distributed Estimation Over Adaptive Networks
Adaptive networks consist of a collection of nodes with adaptation and learning abilities. The nodes interact with each other on a local level and diffuse information across the network to solve estimation and inference tasks in a distributed manner. In this work, we compare the mean-square performance of two main strategies for distributed estimation over networks: consensus strategies and diffusion strategies. The analysis in the paper confirms that under constant step-sizes, diffusion strategies allow information to diffuse more thoroughly through the network and this property has a favorable effect on the evolution of ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Generalized Orthogonal Matching Pursuit
As a greedy algorithm to recover sparse signals from compressed measurements, orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In this paper, we introduce an extension of the OMP for pursuing efficiency in reconstructing sparse signals. Our approach, henceforth referred to as generalized OMP (gOMP), is literally a generalization of the OMP in the sense that multiple $N$ indices are identified per iteration. Owing to the selection of multiple “correct” indices, the gOMP algorithm is finished with much smaller number of iterations when compared to the OMP. We show that th...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Radar Maneuvering Target Motion Estimation Based on Generalized Radon-Fourier Transform
The slant range of a radar maneuvering target is usually modeled as a multivariate function in terms of its illumination time and multiple motion parameters. This multivariate range function includes the modulations on both the envelope and the phase of an echo of the coherent radar target and provides the foundation for radar target motion estimation. In this paper, the maximum likelihood estimators (MLE) are derived for motion estimation of a maneuvering target based on joint envelope and phase measurement, phase-only measurement and envelope-only measurement in case of high signal-to-noise ratio (SNR), respectively. It ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Geodesic Convexity and Covariance Estimation
Geodesic convexity is a generalization of classical convexity which guarantees that all local minima of g-convex functions are globally optimal. We consider g-convex functions with positive definite matrix variables, and prove that Kronecker products, and logarithms of determinants are g-convex. We apply these results to two modern covariance estimation problems: robust estimation in scaled Gaussian distributions, and Kronecker structured models. Maximum likelihood estimation in these settings involves non-convex minimizations. We show that these problems are in fact g-convex. This leads to straight forward analysis, allow...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

A Novel Location-Penalized Maximum Likelihood Estimator for Bearing-Only Target Localization
In this paper, we present a location-penalized maximum likelihood (LPML) estimator for bearing only target localization. We develop a new penalized maximum likelihood cost function by transforming the variables of target position and bearings. The new penalized likelihood function can also be recognized as a posterior distribution under a Bayesian framework by penalizing a prior. We give analysis of the asymptotic properties and show that both traditional bearing maximum likelihood (TBML) and LPML estimators are asymptotically efficient estimators. To compare the performances of the TBML and LPML estimators, we analyze the...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Minimax-Optimal Hypothesis Testing With Estimation-Dependent Costs
The objective is to decide between two hypotheses, where each one involves unknown parameters that are of interest to be estimated. The existing approaches on detection and estimation place the primary emphasis on the detection part by solving this part optimally and treating the estimation part suboptimally. The proposed framework, in contrast, treats both problems simultaneously and in a jointly optimal manner. The resulting test exhibits the flexibility to strike any desired balance between the detection and estimation accuracies. By exploiting this flexibility, depending on the application in hand, this new technique o...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Moment Estimation Using a Marginalized Transform
We present a method for estimating mean and covariance of a transformed Gaussian random variable. The method is based on evaluations of the transforming function and resembles the unscented transform and Gauss-Hermite integration in that respect. The information provided by the evaluations is used in a Bayesian framework to form a posterior description of the parameters in a model of the transforming function. Estimates are then derived by marginalizing these parameters from the analytical expression of the mean and covariance. An estimation algorithm, based on the assumption that the transforming function can be described...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Multiple Quadrature Kalman Filtering
Bayesian filtering is a statistical approach that naturally appears in many signal processing problems. Ranging from Kalman filter to particle filters, there is a plethora of alternatives depending on model assumptions. With the exception of very few tractable cases, one has to resort to suboptimal methods due to the inability to analytically compute the Bayesian recursion in general dynamical systems. This is why it has attracted the attention of many researchers in order to develop efficient algorithms to implement it. We focus our interest into a recently developed algorithm known as the Quadrature Kalman filter (QKF). ...
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Signal Processing publication information
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

Table of Contents
Source: IEEE Transactions on Signal Processing - December 1, 2012 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Medical Imaging information for authors
Source: IEE Transactions on Medical Imaging - December 1, 2012 Category: Biomedical Engineering Source Type: research