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Signal Processing, IEEE Transactions on

Issue 3 • Date March 2006

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Displaying Results 1 - 25 of 38
  • Table of contents

    Publication Year: 2006 , Page(s): c1 - c4
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  • IEEE Transactions on Signal Processing publication information

    Publication Year: 2006 , Page(s): c2
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  • An asymptotically unbiased estimator for bearings-only and Doppler-bearing target motion analysis

    Publication Year: 2006 , Page(s): 809 - 822
    Cited by:  Papers (27)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (552 KB)  

    Bearings-only (BO) and Doppler-bearing (DB) target motion analysis (TMA) attempt to obtain a target trajectory based on bearings and on Doppler and bearing measurements, respectively, from an observer to the target. The BO-TMA and DB-TMA problems are nontrivial because the measurement equations are nonlinearly related to the target location parameters. The pseudolinear formulation provides a linear estimator solution, but the resulting location estimate is biased. The instrumental variable method and the numerical maximum likelihood approach can eliminate the bias. Their convergence behavior, however, is not easy to control. This paper proposes an asymptotically unbiased estimator of the tracking problem. The proposed method applies least squares minimization on the pseudolinear equations with a quadratic constraint on the unknown parameters. The resulting estimator is shown to be solving the generalized eigenvalue problem. The proposed solution does not require initial guesses and does not have convergence problems. Sequential forms of the proposed algorithms for both BO-TMA and DB-TMA are derived. The sequential algorithms improve the estimation accuracy as a new measurement arrives and do not require generalized eigenvalue decomposition for solution update. The proposed estimator achieves the Cramer-Rao Lower Bound (CRLB) asymptotically for Gaussian noise before the thresholding effect occurs. View full abstract»

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  • Spatial diversity in radars-models and detection performance

    Publication Year: 2006 , Page(s): 823 - 838
    Cited by:  Papers (437)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (608 KB)  

    Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this proposal introduces the statistical MIMO radar concept. To the authors' knowledge, this is the first time that the statistical MIMO is being proposed for radar. The fundamental difference between statistical MIMO and other radar array systems is that the latter seek to maximize the coherent processing gain, while statistical MIMO radar capitalizes on the diversity of target scattering to improve radar performance. Coherent processing is made possible by highly correlated signals at the receiver array, whereas in statistical MIMO radar, the signals received by the array elements are uncorrelated. Radar targets generally consist of many small elemental scatterers that are fused by the radar waveform and the processing at the receiver, to result in echoes with fluctuating amplitude and phase. It is well known that in conventional radar, slow fluctuations of the target radar cross section (RCS) result in target fades that degrade radar performance. By spacing the antenna elements at the transmitter and at the receiver such that the target angular spread is manifested, the MIMO radar can exploit the spatial diversity of target scatterers opening the way to a variety of new techniques that can improve radar performance. This paper focuses on the application of the target spatial diversity to improve detection performance. The optimal detector in the Neyman-Pearson sense is developed and analyzed for the statistical MIMO radar. It is shown that the optimal detector consists of noncoherent processing of the receiver sensors' outputs and that for cases of practical interest, detection performance is superior to that obtained through coherent processing. An optimal detector invariant to the signal and noise levels is also developed and analyzed. In this case as well, statistical MIMO radar provides great improvements over other types of array radars. View full abstract»

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  • Bayesian regularization and nonnegative deconvolution for room impulse response estimation

    Publication Year: 2006 , Page(s): 839 - 847
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (400 KB) |  | HTML iconHTML  

    This paper proposes Bayesian Regularization And Nonnegative Deconvolution (BRAND) for accurately and robustly estimating acoustic room impulse responses for applications such as time-delay estimation and echo cancellation. Similar to conventional deconvolution methods, BRAND estimates the coefficients of convolutive finite-impulse-response (FIR) filters using least-square optimization. However, BRAND exploits the nonnegative, sparse structure of acoustic room impulse responses with nonnegativity constraints and L1-norm sparsity regularization on the filter coefficients. The optimization problem is modeled within the context of a probabilistic Bayesian framework, and expectation-maximization (EM) is used to derive efficient update rules for estimating the optimal regularization parameters. BRAND is demonstrated on two representative examples, subsample time-delay estimation in reverberant environments and acoustic echo cancellation. The results presented in this paper show the advantages of BRAND in high temporal resolution and robustness to ambient noise compared with other conventional techniques. View full abstract»

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  • Joint space-time interpolation for distorted linear and bistatic array geometries

    Publication Year: 2006 , Page(s): 848 - 860
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB) |  | HTML iconHTML  

    This paper presents a new joint space-time interpolation technique (STINT) to improve the small sample support performance of space-time adaptive processing (STAP) with distorted linear monostatic arrays and linear bistatic array configurations. Brennan's rule for the space-time clutter covariance matrix rank is extended to monostatic linear arrays with arbitrary intersensor spacing, distorted linear arrays and bistatic geometries. It is shown that both distortion in the array geometry and bistatic operation increase the clutter rank and cause the space-time clutter covariance matrix to become range dependent. This results in lower output signal-to-interference-plus-noise ratio (SINR) for the same number of adaptive degrees of freedom and reduced available sample support. This motivates the development of the STINT technique aimed at compensating for the clutter rank inflation, while also making the clutter statistics appear more stationary across range. More specifically, a linear transformation is designed that maps the received clutter across space and time to that which would be received by a "virtual" monostatic side-looking ULA. By mapping the data to form a reduced rank clutter covariance matrix, fewer snapshots are needed for a statistically stable matrix inversion as required in STAP, thereby improving the short observation time performance. Simulation results for a typical airborne radar scenario indicate up to 10-dB SINR improvement can be obtained using STINT with limited sample support. View full abstract»

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  • Whitening-rotation-based semi-blind MIMO channel estimation

    Publication Year: 2006 , Page(s): 861 - 869
    Cited by:  Papers (43)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (440 KB) |  | HTML iconHTML  

    This paper proposes a whitening-rotation (WR)-based algorithm for semi-blind estimation of a complex flat-fading multi-input multi-output (MIMO) channel matrix H. The proposed algorithm is based on decomposition of H as the matrix product H=WQH, where W is a whitening matrix and Q is unitary rotation matrix. The whitening matrix W can be estimated blind using only received data while Q is estimated exclusively from pilot symbols. Employing the results for the complex-constrained Cramer-Rao Bound (CC-CRB), it is shown that the lower bound on the mean-square error (MSE) in the estimate of H is directly proportional to its number of unconstrained parameters. Utilizing the bounds, the semi-blind scheme is shown to be very efficient when the number of receive antennas is greater than or equal to the number of transmit antennas. Closed-form expressions for the CRB of the semi-blind technique are presented. Algorithms for channel estimation based on the decomposition are also developed and analyzed. In particular, the properties of the constrained maximum-likelihood (ML) estimator of Q for an orthogonal pilot sequence is examined, and the constrained estimator for a general pilot sequence is derived. In addition, a Gaussian likelihood function is considered for the joint optimization of W and Q, and its performance is studied. Simulation results are presented to support the algorithms and analysis, and they demonstrate improved performance compared to exclusively training-based estimation. View full abstract»

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  • New insights into optimal widely linear array receivers for the demodulation of BPSK, MSK, and GMSK signals corrupted by noncircular interferences-application to SAIC

    Publication Year: 2006 , Page(s): 870 - 883
    Cited by:  Papers (56)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (512 KB)  

    For nonstationary observations, potentially second-order (SO) noncircular, the SO optimal complex filters are time variant and, under some conditions of noncircularity, widely linear (WL). For more than a decade, there has been an increasing interest in optimal WL filters in radiocommunications contexts involving rectilinear signals such as binary phase-shift keying (BPSK) signals. In particular, it has been pointed out that single antenna interference cancellation (SAIC) may be performed by such filters in the context of BPSK cellular networks. Recently, it has been shown that, by a simple algebraic operation of demodulation on the baseband signal, the minimum shift keying (MSK) and Gaussian MSK (GMSK) modulations can be made to approximately correspond to a BPSK modulation, allowing the application of the SAIC concept to the GSM cellular network at the mobile level, being currently studied for standardization, and offering significant improvements of the network's capacity. Despite the increasing interest in optimal WL filters in rectilinear or quasi-rectilinear contexts, many questions about their behavior and their performance have still arisen. The purpose of this paper is to gain insight into the behavior, properties, and performance of optimal WL array receivers, and thus of the SAIC technology, for the demodulation of BPSK, MSK, and GMSK signals corrupted by noncircular interferences. View full abstract»

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  • Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals

    Publication Year: 2006 , Page(s): 884 - 893
    Cited by:  Papers (199)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB)  

    In this paper, we study the performance of multiple-input multiple-output channel estimation methods using training sequences. We consider the popular linear least squares (LS) and minimum mean-square-error (MMSE) approaches and propose new scaled LS (SLS) and relaxed MMSE techniques which require less knowledge of the channel second-order statistics and/or have better performance than the conventional LS and MMSE channel estimators. The optimal choice of training signals is investigated for the aforementioned techniques. In the case of multiple LS channel estimates, the best linear unbiased estimation (BLUE) scheme for their linear combining is developed and studied. View full abstract»

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  • Blind channel identification with colored sources by exploiting properties of companion matrices

    Publication Year: 2006 , Page(s): 894 - 906
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    This paper proposes a new second-order statistics-based method for blind multiple-input multiple-output (MIMO) finite-impulse-response (FIR) channel estimation driven by colored sources. It is assumed that the second-order statistics (SOS) of the input sources are known a priori. By exploiting the new derived properties of the companion matrices, an original proof for the uniqueness of the system solution is provided, which serves as a theoretical basis for the proposed new method that admits a closed-form solution. The corresponding identifiability conditions and the computational complexity of the proposed method are discussed and compared with other existing method. Numerical simulation results are presented to illustrate the performance of the proposed algorithm. View full abstract»

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  • On the asymptotic performance analysis of subspace DOA estimation in the presence of modeling errors: case of MUSIC

    Publication Year: 2006 , Page(s): 907 - 920
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (688 KB) |  | HTML iconHTML  

    This paper provides a new analytic expression of the bias and RMS error (root mean square) error of the estimated direction of arrival (DOA) in the presence of modeling errors. In , first-order approximations of the RMS error are derived, which are accurate for small enough perturbations. However, the previously available expressions are not able to capture the behavior of the estimation algorithm into the threshold region. In order to fill this gap, we provide a second-order performance analysis, which is valid in a larger interval of modeling errors. To this end, it is shown that the DOA estimation error for each signal source can be expressed as a ratio of Hermitian forms, with a stochastic vector containing the modeling error. Then, an analytic expression for the moments of such a Hermitian forms ratio is provided. Finally, a closed-form expression for the performance (bias and RMS error) is derived. Simulation results indicate that the new result is accurate into the region where the algorithm breaks down. View full abstract»

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  • Lapped unimodular transforms: lifting factorization and structural regularity

    Publication Year: 2006 , Page(s): 921 - 931
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (816 KB)  

    In this paper, the lifting factorization and structural regularity of the lapped unimodular transforms (LUTs) are studied. The proposed M-channel lifting factorization is complete, is minimal in the McMillan sense, and has diagonal entries of unity. In addition to allowing for integer-to-integer mapping and guaranteeing perfect reconstruction even under finite precision, the proposed lifting factorization structurally ensures unimodularity. For regular LUT design, structural conditions that impose (1,1)-, (1,2)- and (2,1)-regularity onto the filter banks (FBs) are presented. Consequently, the optimal filter coefficients can be obtained through unconstrained optimizations. A special lifting-based lattice structure is used for parameterizing nonsingular matrices, which not only helps impose regularity but also has rational-coefficient unimodular FBs as a by-product. The regular LUTs can be transformed to the lifting domain with the proposed factorization for faster and multiplierless implementations. The lifting factorization and the regularity conditions are derived for two different (Type-I and Type-II) factorizations of the first-order unimodular FBs. Design examples are presented to confirm the proposed theory. View full abstract»

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  • Efficient sample rate conversion for software radio systems

    Publication Year: 2006 , Page(s): 932 - 939
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB) |  | HTML iconHTML  

    An efficient sample rate conversion (SRC) method for software radio (SWR) systems is proposed. The proposed method modifies conventional single- or multistage SRC processes such that the computation of the output of a particular stage is performed in a hierarchical fashion. This SRC method consumes fewer computations than traditional SRC methods over a range of SRC factors and is especially suitable for SWR base station transmitters. The computational requirements of the proposed SRC method and conventional SRC methods are compared and simulation results of the proposed method are discussed. View full abstract»

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  • Everything you always wanted to know about training: guidelines derived using the affine precoding framework and the CRB

    Publication Year: 2006 , Page(s): 940 - 954
    Cited by:  Papers (27)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (576 KB) |  | HTML iconHTML  

    In this paper, affine precoding is used to investigate the tradeoffs that exist while using the transmitter resources on training versus information symbols. The channel input is a training vector superimposed on a linearly precoded vector of symbols. A block-fading frequency-selective multi-input multi-output (MIMO) channel is considered. To highlight the tradeoffs between training and data symbols, the Fisher information matrix (FIM) is derived under two circumstances: the random parameter vector to be estimated contains 1) only fading channel coefficients and 2) unknown data symbols as well as the channel coefficients. While strategy 1 corresponds to the receiver structure in which the channel is estimated initially and the channel measurement is utilized to retrieve the data symbols, strategy 2 corresponds to the structure in which channel and symbol estimations are performed jointly. The interesting outcome of the study in this paper is that minimizing the channel Cramer-Rao bound (CRB) for strategies 1 and 2 under a total average transmit power constraint leads to different affine precoder design guidelines. View full abstract»

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  • NEDA: a low-power high-performance DCT architecture

    Publication Year: 2006 , Page(s): 955 - 964
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1064 KB) |  | HTML iconHTML  

    Conventional distributed arithmetic (DA) is popular in application-specific integrated circuit (ASIC) design, and it features on-chip ROM to achieve high speed and regularity. In this paper, a new DA architecture called NEDA is proposed, aimed at reducing the cost metrics of power and area while maintaining high speed and accuracy in digital signal processing (DSP) applications. Mathematical analysis proves that DA can implement inner product of vectors in the form of two's complement numbers using only additions, followed by a small number of shifts at the final stage. Comparative studies show that NEDA outperforms widely used approaches such as multiply/accumulate (MAC) and DA in many aspects. Being a high-speed architecture free of ROM, multiplication, and subtraction, NEDA can also expose the redundancy existing in the adder array consisting of entries of 0 and 1. A hardware compression scheme is introduced to generate a butterfly structure with minimum number of additions. NEDA-based architectures for 8 × 8 discrete cosine transform (DCT) core are presented as an example. Savings exceeding 88% are achieved, when the compression scheme is applied along with NEDA. Finite word-length simulations demonstrate the viability and excellent performance of NEDA. View full abstract»

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  • Design of block transceivers with decision feedback detection

    Publication Year: 2006 , Page(s): 965 - 978
    Cited by:  Papers (43)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (632 KB) |  | HTML iconHTML  

    This paper presents a method for jointly designing the transmitter-receiver pair in a block-by-block communication system that employs (intrablock) decision feedback detection. We provide closed-form expressions for transmitter-receiver pairs that simultaneously minimize the arithmetic mean squared error (MSE) at the decision point (assuming perfect feedback), the geometric MSE, and the bit error rate of a uniformly bit-loaded system at moderate-to-high signal-to-noise ratios. Separate expressions apply for the "zero-forcing" and "minimum MSE" (MMSE) decision feedback structures. In the MMSE case, the proposed design also maximizes the Gaussian mutual information and suggests that one can approach the capacity of the block transmission system using (independent instances of) the same (Gaussian) code for each element of the block. Our simulation studies indicate that the proposed transceivers perform significantly better than standard transceivers and that they retain their performance advantages in the presence of error propagation. View full abstract»

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  • Estimation and equalization of doubly selective channels using known symbol padding

    Publication Year: 2006 , Page(s): 979 - 990
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (592 KB) |  | HTML iconHTML  

    This paper considers the situation where users that experience high-mobility transmit data over frequency-selective channels, resulting in a doubly selective channel model (i.e., time- and frequency-selective channels) and this within the framework of Known Symbol Padding (KSP) transmission. KSP is a recently proposed block transmission technique where short sequences of known symbols acting as guard bands are inserted between successive blocks of data symbols. This paper proposes three novel channel estimation methods that allow for an accurate estimation of the time-varying transmission channel solely relying on the knowledge of the redundant symbols introduced by the KSP transmission scheme. The first method is a direct adaptive one while the others rely on a recently proposed model, the Basis Expansion Model (BEM), where the doubly selective channel is approximated with high accuracy using a limited number of complex exponentials. An important characteristic of the proposed methods is that they exploit all the received symbols that contain contributions from the training sequences and blindly filter out the contribution of the unknown surrounding data symbols. Besides these channel identification methods, the classical KSP equalizers are adapted to the context of doubly selective channels, which allows evaluation of the bit-error-rate (BER) performance of a KSP transmission system relying on the proposed channel estimation methods in the context of doubly selective channels. Simulation results show that KSP transmission is indeed a suitable transmission technique toward the delivery of high data rates to users experiencing a high mobility, when adapted KSP equalizers are used in combination with the proposed channel estimation methods. View full abstract»

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  • Block error correcting codes using finite-field wavelet transforms

    Publication Year: 2006 , Page(s): 991 - 1004
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (784 KB) |  | HTML iconHTML  

    This paper extends the popular wavelet framework for signal representation to error control coding. The primary goal of the paper is to use cyclic finite-field wavelets and filter banks to study arbitrary-rate L-circulant codes. It is shown that the wavelet representation leads to an efficient implementation of the block code encoder and the syndrome generator. A formulation is then given for constructing maximum-distance separable (MDS) wavelet codes using frequency-domain constraints. This paper also studies the possibility of finding a wavelet code whose tail-biting trellis is efficient for soft-decision decoding. The wavelet method may provide an easy way to look for such codes. View full abstract»

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  • A pseudorandom postfix OFDM modulator - semi-blind channel estimation and equalization

    Publication Year: 2006 , Page(s): 1005 - 1017
    Cited by:  Papers (26)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (648 KB) |  | HTML iconHTML  

    This paper details a new orthogonal-frequency-division-multiplexing (OFDM) modulator based on the use of a pseudorandom postfix (PRP)-OFDM and discusses low-complexity equalization and channel estimation/tracking architectures. The main property of this new modulation scheme is the ability to estimate and track the channel variations semi-blindly using order-one statistics of the received signal. Compared with known cyclic prefix OFDM (CP-OFDM) pilot-symbol-assisted modulation (PSAM) schemes, the pilot overhead is avoided: The channel estimation is performed based on the exploitation of pseudorandomly weighted postfix sequences replacing the guard interval contents of CP-OFDM. PRP-OFDM is shown to be of advantage if the target application requires 1) a minimum pilot overhead, 2) low-complexity channel tracking (e.g., high mobility context), and 3) adjustable receiver complexity/performance trade-offs (available due to the similarities of PRP-OFDM to the zero-padded OFDM (ZP-OFDM) modulation scheme) without requiring any feedback loop to the transmitter. View full abstract»

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  • Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks

    Publication Year: 2006 , Page(s): 1018 - 1027
    Cited by:  Papers (102)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    In this paper, we revisit the problem of fusing decisions transmitted over fading channels in a wireless sensor network. Previous development relies on instantaneous channel state information (CSI). However, acquiring channel information may be too costly for resource constrained sensor networks. In this paper, we propose a new likelihood ratio (LR)-based fusion rule which requires only the knowledge of channel statistics instead of instantaneous CSI. Based on the assumption that all the sensors have the same detection performance and the same channel signal-to-noise ratio (SNR), we show that when the channel SNR is low, this fusion rule reduces to a statistic in the form of an equal gain combiner (EGC), which explains why EGC is a very good choice with low or medium SNR; at high-channel SNR, it is equivalent to the Chair-Varshney fusion rule. Performance evaluation shows that the new fusion rule exhibits only slight performance degradation compared with the optimal LR-based fusion rule using instantaneous CSI. View full abstract»

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  • Sequential blind source separation based exclusively on second-order statistics developed for a class of periodic signals

    Publication Year: 2006 , Page(s): 1028 - 1040
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (784 KB) |  | HTML iconHTML  

    A sequential algorithm for the blind separation of a class of periodic source signals is introduced in this paper. The algorithm is based only on second-order statistical information and exploits the assumption that the source signals have distinct periods. Separation is performed by sequentially converging to a solution which in effect diagonalizes the output covariance matrix constructed at a lag corresponding to the fundamental period of the source we select, the one with the smallest period. Simulation results for synthetic signals and real electrocardiogram recordings show that the proposed algorithm has the ability to restore statistical independence, and its performance is comparable to that of the equivariant adaptive source separation (EASI) algorithm, a benchmark high-order statistics-based sequential algorithm with similar computational complexity. The proposed algorithm is also shown to mitigate the limitation that the EASI algorithm can separate at most one Gaussian distributed source. Furthermore, the steady-state performance of the proposed algorithm is compared with that of EASI and the block-based second-order blind identification (SOBI) method. View full abstract»

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  • Performance analysis of estimation algorithms of nonstationary ARMA processes

    Publication Year: 2006 , Page(s): 1041 - 1053
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB)  

    The correlation analysis based methods are not suitable for identifying parameters of nonstationary autoregressive (AR), moving average (MA), and ARMA systems. By using estimation residuals in place of unmeasurable noise terms in information vector or matrix, we develop a least squares based and gradient based algorithms and establish the consistency of the proposed algorithms without assuming noise stationarity, ergodicity, or existence of higher order moments. Furthermore, we derive the conditions for convergence of the parameter estimation. The simulation results validate the convergence theorems proposed. View full abstract»

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  • Blind channel estimation in MIMO OFDM systems with multiuser interference

    Publication Year: 2006 , Page(s): 1054 - 1068
    Cited by:  Papers (21)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (480 KB) |  | HTML iconHTML  

    This paper proposes a blind channel estimation method in the context of a multiuser orthogonal-frequency-domain-multiplexing (OFDM) system, where each user transmits utilizing all available subcarriers. A linear nonredundant block precoding scheme is applied at the input of the OFDM system. The precoding spreads the symbols of each user over all subcarriers, thus increasing multipath diversity. At the same time, it introduces a structure to the transmitted symbols, which is exploited at the receiver to estimate the channel in a blind fashion. The proposed channel estimation approach employs computationally simple cross-correlation operations and yields the channel up to a diagonal ambiguity. It does not require channel length information and is not sensitive to additive stationary noise. The precoding does not increase transmission power and maintains even distribution of power between OFDM blocks. A general description of precoding matrices is provided as well as analytical expressions of symbol error probability and signal-to-interference ratio, which could be used to obtain optimum precoding schemes. View full abstract»

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  • Optimal and robust noncausal filter formulations

    Publication Year: 2006 , Page(s): 1069 - 1077
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (280 KB) |  | HTML iconHTML  

    The paper describes an optimal minimum-variance noncausal filter or fixed-interval smoother. The optimal solution involves a cascade of a Kalman predictor and an adjoint Kalman predictor. A robust smoother involving H predictors is also described. Filter asymptotes are developed for output estimation and input estimation problems which yield bounds on the spectrum of the estimation error. These bounds lead to a priori estimates for the scalar γ in the H filter and smoother design. The results of simulation studies are presented, which demonstrate that optimal, robust, and extended Kalman smoothers can provide performance benefits. View full abstract»

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  • Mean-square performance of a convex combination of two adaptive filters

    Publication Year: 2006 , Page(s): 1078 - 1090
    Cited by:  Papers (126)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (584 KB)  

    Combination approaches provide an interesting way to improve adaptive filter performance. In this paper, we study the mean-square performance of a convex combination of two transversal filters. The individual filters are independently adapted using their own error signals, while the combination is adapted by means of a stochastic gradient algorithm in order to minimize the error of the overall structure. General expressions are derived that show that the method is universal with respect to the component filters, i.e., in steady-state, it performs at least as well as the best component filter. Furthermore, when the correlation between the a priori errors of the components is low enough, their combination is able to outperform both of them. Using energy conservation relations, we specialize the results to a combination of least mean-square filters operating both in stationary and in nonstationary scenarios. We also show how the universality of the scheme can be exploited to design filters with improved tracking performance. View full abstract»

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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

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Meet Our Editors

Editor-in-Chief
Sergios Theodoridis
University of Athens