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Signal Processing, IEEE Transactions on

Issue 4 • Date April 2004

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Displaying Results 1 - 25 of 33
  • Table of contents

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

    Page(s): c2
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  • Second-order blind separation of first- and second-order cyclostationary sources-application to AM, FSK, CPFSK, and deterministic sources

    Page(s): 845 - 861
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (576 KB) |  | HTML iconHTML  

    Most of the second-order (SO) and higher order (HO) blind source separation (BSS) methods developed this last decade aim at blindly separating statistically independent sources that are assumed zero-mean, stationary, and ergodic. Nevertheless, in many situations of practical interest, such as in radiocommunications contexts, the sources are nonstationary and very often cyclostationary (digital modulations). The behavior of the current SO and fourth-order (FO) cumulant-based BSS methods in the presence of cyclostationary sources has been analyzed, recently, in a previous paper by Ferre´ol and Chevalier, assuming zero-mean sources. However, some cyclostationary sources used in practical situations are not zero-mean but have a first-order (FIO) cyclostationarity property, which is, in particular, the case for some amplitude modulated (AM) signals and for some nonlinearly modulated digital sources such as frequency shift keying (FSK) or some continuous phase frequency shift keying (CPFSK) sources. For such sources, the results presented in the previous paper by Ferre´ol and Chevalier no longer hold, and the purpose of this paper is to analyze the behavior and to propose adaptations of the current SO BSS methods for sources that are both FIO and SO cyclostationary and cyclo-ergodic. An extension for deterministic sources is also proposed in the paper. View full abstract»

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  • Cramer-Rao bounds for the estimation of multipath parameters and mobiles' positions in asynchronous DS-CDMA systems

    Page(s): 862 - 875
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (472 KB) |  | HTML iconHTML  

    Commercial applications for the location of subscribers of wireless services continue to expand. Consequently, finding the Cramer-Rao lower bound (CRLB), which serves as an optimality criterion for the location estimation problem, is of interest. In this paper, we derive the deterministic CRLBs for the estimation of the specular multipath parameters and the positions of the mobiles in an asynchronous direct sequence code division multiple access (DS-CDMA) system operating over specular multipath fading channels. We assume a multilateral radio location system where the location estimates are obtained from some or all of the estimated signal parameters at different clusters of antennas of arbitrary geometry. Extension for unilateral and composite radio location techniques is also discussed. As an application example, we use numerical simulations to investigate the effects of specular multipath and multiple access interference (MAI) on the positioning accuracy for different radio location techniques. View full abstract»

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  • Computationally efficient subspace-based method for direction-of-arrival estimation without eigendecomposition

    Page(s): 876 - 893
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    A computationally simple direction-of-arrival (DOA) estimation method with good statistical performance is attractive in many practical applications of array processing. In this paper, we propose a new computationally efficient subspace-based method without eigendecomposition (SUMWE) for the coherent narrowband signals impinging on a uniform linear array (ULA) by exploiting the array geometry and its shift invariance property. The coherency of incident signals is decorrelated through subarray averaging, and the space is obtained through a linear operation of a matrix formed from the cross-correlations between some sensor data, where the effect of additive noise is eliminated. Consequently, the DOAs can be estimated without performing eigendecomposition, and there is no need to evaluate all correlations of the array data. Furthermore, the SUMWE is also suitable for the case of partly coherent or incoherent signals, and it can be extended to the spatially correlated noise by choosing appropriate subarrays. The statistical analysis of the SUMWE is studied, and the asymptotic mean-squared-error (MSE) expression of the estimation error is derived. The performance of the SUMWE is demonstrated, and the theoretical analysis is substantiated through numerical examples. It is shown that the SUMWE is superior in resolving closely spaced coherent signals with a small number of snapshots and at low signal-to-noise ratio (SNR) and offers good estimation performance for both uncorrelated and correlated incident signals. View full abstract»

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  • Optimization of nonlinear signal constellations for real-world MIMO channels

    Page(s): 894 - 902
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB) |  | HTML iconHTML  

    The performance of spatial multiplexing (SM) multiple-input multiple-output (MIMO) communication systems is highly dependent on the richness of scattering, the presence of dominant components, and the interelement spacings. In this paper, a new interpretation of the impact of transmit correlation on the performance of SM is given based on a so-called "symbol-related array factor." Nonlinear signal constellations for SM over real-world fading channels are then designed by minimizing an estimate of the average symbol error rate under an average transmit power constraint. The new transmission scheme exploits the spectral efficiency advantage of SM and the robustness of eigen-beamforming. Through simulations, it is shown to be more robust against fading correlations and high Ricean K-factors than SM using the classical phase shift keying (PSK) and quadrature amplitude modulation (QAM) constellations. The symbol error rate performance of this scheme is not affected by a change in the propagation environment or the interelement distance. Furthermore, if the scheme is used on the uplink, no explicit rate-consuming feedback link from the base station to the mobile station is required. View full abstract»

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  • Multiple radar targets detection by exploiting induced amplitude modulation

    Page(s): 903 - 913
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    This work deals with the problem of detecting and estimating multiple radar targets present in the same range-azimuth resolution cell of a surveillance radar system with a mechanically rotating antenna. In the first part of the work, we tackled the problem of estimating target complex amplitudes, Doppler frequencies, and directions of arrival, and a consistent estimator based on the asymptotic maximum likelihood (AML) method was derived. In this second part, we tackle the "detection problem," which consists of determining the number of targets. First, the target parameters are estimated, assuming a maximum number of possible targets. Subsequently, these estimates are used in a successive hypotheses test procedure. The statistic of the test at each step of the procedure is derived by using an asymptotic expression of the generalized likelihood ratio test (GLRT) statistic. Performance of the proposed algorithm is investigated through both asymptotical analysis (as concerning the probability of false alarm) and Monte Carlo simulation. View full abstract»

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  • A matrix-valued wavelet KL-like expansion for wide-sense stationary random processes

    Page(s): 914 - 920
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    Matrix-valued wavelet series expansions for wide-sense stationary processes are studied in this paper. The expansion coefficients a are uncorrelated matrix random process, which is a property similar to that of a matrix Karhunen-Loe`ve (MKL) expansion. Unlike the MKL expansion, however, the matrix wavelet expansion does not require the solution of the eigen equation. This expansion also has advantages over the Fourier series, which is often used as an approximation to the MKL expansion in that it completely eliminates correlation. The basis functions of this expansion can be obtained easily from wavelets of the Matrix-valued Lemarie´-Meyer type and the power-spectral density of the process. View full abstract»

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  • Approximation error of shifted signals in spline spaces

    Page(s): 921 - 928
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    Spline signal spaces offer several advantages for the representation of signals compared with the more traditional signal spaces of bandlimited signals. Among them are the finite support of B-splines, simple manipulations like differentiation and integration, etc. A major disadvantage, however, is that spline signal spaces are not closed under signal shifts. In order to assess the approximation error introduced by shifting a spline signal, the approximation error norm and its average are evaluated. Furthermore, an upper bound on the expected normalized approximation error is derived using Reid's inequality. View full abstract»

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  • Signal enhancement by time-frequency peak filtering

    Page(s): 929 - 937
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (928 KB) |  | HTML iconHTML  

    Time-frequency peak filtering (TFPF) allows the reconstruction of signals from observations corrupted by additive noise by encoding the noisy signal as the instantaneous frequency (IF) of a frequency modulated (FM) analytic signal. IF estimation is then performed on the analytic signal using the peak of a time-frequency distribution (TFD) to recover the filtered signal. This method is biased when the peak of the Wigner-Ville distribution (WVD) is used to estimate the encoded signal's instantaneous frequency. We characterize a class of signals for which the method implemented using the pseudo WVD is approximately unbiased. This class contains deterministic bandlimited nonstationary multicomponent signals in additive white Gaussian noise (WGN). We then derive the pseudo WVD window length that gives a reduced bias when TFPF is used for signals from this class. Testing of the method on both synthetic and real life newborn electroencephalogram (EEG) signals shows clean recovery of the signals in noise level down to a signal-to-noise ratio (SNR) of -9 dB. View full abstract»

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  • Partial-update NLMS algorithms with data-selective updating

    Page(s): 938 - 949
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (584 KB) |  | HTML iconHTML  

    In this paper, we present mean-squared convergence analysis for the partial-update normalized least-mean square (PU-NLMS) algorithm with closed-form expressions for the case of white input signals. The formulae presented here are more accurate than the ones found in the literature for the PU-NLMS algorithm. Thereafter, the ideas of the partial-update NLMS-type algorithms found in the literature are incorporated in the framework of set-membership filtering, from which data-selective NLMS-type algorithms with partial-update are derived. The new algorithms, referred to herein as the set-membership partial-update normalized least-mean square (SM-PU-NLMS) algorithms, combine the data-selective updating from set-membership filtering with the reduced computational complexity from partial updating. A thorough discussion of the SM-PU-NLMS algorithms follows, whereby we propose different update strategies and provide stability analysis and closed-form formulae for excess mean-squared error (MSE). Simulation results verify the analysis for the PU-NLMS algorithm and the good performance of the SM-PU-NLMS algorithms in terms of convergence speed, final misadjustment, and computational complexity. View full abstract»

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  • Spectrum estimation from quantum-limited interferograms

    Page(s): 950 - 961
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    A quantitative model for interferogram data collected in a quantum-limited hyperspectral imaging system is derived. This model accounts for the geometry of the interferometer, the Poisson noise, and the parameterization of the mean of the noise in terms of the autocorrelation function of the incident optical signal. The Crame´r-Rao bound on the variance of unbiased spectrum estimates is derived and provides an explanation for what is often called the "multiplex disadvantage" in interferometer-based methods. Three spectrum estimation algorithms are studied: maximum likelihood via the expectation-maximization (EM) algorithm, least squares (LS), and the fast Fourier transform (FFT) with data precorrection. Extensive simulation results reveal advantages and disadvantages with all three methods in different signal-to-noise ratio (SNR) regimes. View full abstract»

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  • Multistage IIR filter design using convex stability domains defined by positive realness

    Page(s): 962 - 974
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (504 KB) |  | HTML iconHTML  

    In this paper, we consider infinite impulse response (IIR) filter design where both magnitude and phase are optimized using a weighted and sampled least-squares criterion. We propose a new convex stability domain defined by positive realness for ensuring the stability of the filter and adapt the Steiglitz-McBride (SM), Gauss-Newton (GN), and classical descent methods to the new stability domain. We show how to describe the stability domain such that the description is suited to semidefinite programming and is implementable exactly; in addition, we prove that this domain contains the domain given by Rouche´'s theorem. Finally, we give experimental evidence that the best designs are usually obtained with a multistage algorithm, where the three above methods are used in succession, each one being initialized with the result of the previous and where the positive realness stability domain is used instead of that defined by Rouche´'s theorem. View full abstract»

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  • A recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: fast algorithm and convergence performance analysis

    Page(s): 975 - 991
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (608 KB) |  | HTML iconHTML  

    This paper studies the problem of robust adaptive filtering in impulsive noise environment using a recursive least M-estimate algorithm (RLM). The RLM algorithm minimizes a robust M-estimator-based cost function instead of the conventional mean square error function (MSE). Previous work has showed that the RLM algorithm offers improved robustness to impulses over conventional recursive least squares (RLS) algorithm. In this paper, the mean and mean square convergence behaviors of the RLM algorithm under the contaminated Gaussian impulsive noise model is analyzed. A lattice structure-based fast RLM algorithm, called the Huber Prior Error Feedback-Least Squares Lattice (H-PEF-LSL) algorithm is derived. Part of the H-PEF-LSL algorithm was presented in ICASSP 2001. It has an order O(N) arithmetic complexity, where N is the length of the adaptive filter, and can be viewed as a fast implementation of the RLM algorithm based on the modified Huber M-estimate function and the conventional PEF-LSL adaptive filtering algorithm. Simulation results show that the transversal RLM and the H-PEF-LSL algorithms have better performance than the conventional RLS and other RLS-like robust adaptive algorithms tested when the desired and input signals are corrupted by impulsive noise. Furthermore, the theoretical and simulation results on the convergence behaviors agree very well with each other. View full abstract»

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  • Fast algorithm for the 3-D DCT-II

    Page(s): 992 - 1001
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB) |  | HTML iconHTML  

    Recently, many applications for three-dimensional (3-D) image and video compression have been proposed using 3-D discrete cosine transforms (3-D DCTs). Among different types of DCTs, the type-II DCT (DCT-II) is the most used. In order to use the 3-D DCTs in practical applications, fast 3-D algorithms are essential. Therefore, in this paper, the 3-D vector-radix decimation-in-frequency (3-D VR DIF) algorithm that calculates the 3-D DCT-II directly is introduced. The mathematical analysis and the implementation of the developed algorithm are presented, showing that this algorithm possesses a regular structure, can be implemented in-place for efficient use of memory, and is faster than the conventional row-column-frame (RCF) approach. Furthermore, an application of 3-D video compression-based 3-D DCT-II is implemented using the 3-D new algorithm. This has led to a substantial speed improvement for 3-D DCT-II-based compression systems and proved the validity of the developed algorithm. View full abstract»

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  • Low-complexity equalization of OFDM in doubly selective channels

    Page(s): 1002 - 1011
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB) |  | HTML iconHTML  

    Orthogonal frequency division multiplexing (OFDM) systems may experience significant inter-carrier interference (ICI) when used in time- and frequency-selective, or doubly selective, channels. In such cases, the classical symbol estimation schemes, e.g., minimum mean-squared error (MMSE) and zero-forcing (ZF) estimation, require matrix inversion that is prohibitively complex for large symbol lengths. An analysis of the ICI generation mechanism leads us to propose a novel two-stage equalizer whose complexity (apart from the FFT) is linear in the OFDM symbol length. The first stage applies optimal linear preprocessing to restrict ICI support, and the second stage uses iterative MMSE estimation to estimate finite-alphabet frequency-domain symbols. Simulation results indicate that our equalizer has significant performance and complexity advantages over the classical linear MMSE estimator in doubly selective channels. View full abstract»

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  • Diagonal block space-time code design for diversity and coding advantage over flat fading channels

    Page(s): 1012 - 1020
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (376 KB) |  | HTML iconHTML  

    The potential promised by multiple transmit antennas has raised considerable interest in space-time coding for wireless communications. In this paper, we propose a systematic approach for designing space-time trellis codes over flat fading channels with full antenna diversity and good coding advantage. It is suitable for an arbitrary number of transmit antennas with arbitrary signal constellations. The key to this approach is to separate the traditional space-time trellis code design into two parts. It first encodes the information symbols using a one-dimensional (M,1) nonbinary block code, with M being the number of transmit antennas, and then transmits the coded symbols diagonally across the space-time grid. We show that regardless of channel time-selectivity, this new class of space-time codes always achieves a transmit diversity of order M with a minimum number of trellis states and a coding advantage equal to the minimum product distance of the employed block code. Traditional delay diversity codes can be viewed as a special case of this coding scheme in which the repetition block code is employed. To maximize the coding advantage, we introduce an optimal construction of the nonbinary block code for a given modulation scheme. In particular, an efficient suboptimal solution for multilevel phase-shift-keying (PSK) modulation is proposed. Some code examples with 2-6 bits/s/Hz and two to six transmit antennas are provided, and they demonstrate excellent performance via computer simulations. Although it is proposed for flat fading channels, this coding scheme can be easily extended to frequency-selective fading channels. View full abstract»

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  • Jointly minimum BER transmitter and receiver FIR MIMO filters for binary signal vectors

    Page(s): 1021 - 1036
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (576 KB) |  | HTML iconHTML  

    A theory is developed for jointly minimizing the bit error rate (BER) between the desired and decoded signals with respect to the coefficients of transmitter and receiver finite impulse response (FIR) multiple-input multiple-output (MIMO) filters. The original signal is assumed to be a vector time-series with equally likely memoryless Bernoulli vector components. The channel model constitutes of a known FIR MIMO transfer function and Gaussian additive noise independent of the original signal. The channel input signal is assumed to be power constrained. Based on the formulas obtained, an iterative numerical optimization algorithm is proposed. When compared with other design methods available in the literature, the proposed method yields better results due to the generality of the model considered and the joint optimization of the transmitter-receiver pair. View full abstract»

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  • Transceiver optimization for block-based multiple access through ISI channels

    Page(s): 1037 - 1052
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB) |  | HTML iconHTML  

    In this paper, we describe a formulation of the minimum mean square error (MMSE) joint transmitter-receiver design problem for block-based multiple access communication over intersymbol interference (ISI) channels. Since the direct formulation of this problem turns out to be nonconvex, we develop various alternative convex formulations using techniques of linear matrix inequalities (LMIs) and second-order cone programming (SOCP). In particular, we show that the optimal MMSE transceiver design problem can be reformulated as a semidefinite program (SDP), which can be solved using highly efficient interior point methods. When the channel matrices are diagonal (as in cyclic prefixed multicarrier systems), we show that the optimal MMSE transceivers can be obtained by subcarrier allocation and optimal power loading to each subcarrier for all the users. Moreover, the optimal subcarrier allocation and power-loading can be computed fairly simply (in polynomial time) by the relative ratios of the magnitudes of the subchannel gains corresponding to all subcarriers. We also prove that any two users can share no more than one subcarrier in the optimal MMSE transceivers. By exploiting this property, we design an efficient strongly polynomial time algorithm for the determination of optimal powerloading and subcarrier allocation in the two-user case. View full abstract»

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  • Blind and semi-blind FIR multichannel estimation: (global) identifiability conditions

    Page(s): 1053 - 1064
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB) |  | HTML iconHTML  

    Two channel estimation methods are often opposed: training sequence methods that use the information induced by known symbols and blind methods that use the information contained in the received signal and, possibly, hypotheses on the input symbol statistics but without integrating the information from known symbols, if present. Semi-blind methods combine both training sequence and blind information and are more powerful than the two methods separately. We investigate the identifiability conditions for blind and semi-blind finite impulse response (FIR) multichannel estimation in terms of channel characteristics, received data length, and input symbol excitation modes, as well as number of known symbols for semi-blind estimation. Two models corresponding to two different cases of a priori knowledge on the input symbols are studied: the deterministic model in which the unknown symbols are considered as unknown deterministic quantities and the Gaussian model in which they are considered as Gaussian random variables. This last model includes the methods using the second-order statistics of the received data. Semi-blind methods appear superior to blind and training sequence methods and allow the estimation of any channel with only few known symbols. Furthermore, the Gaussian model appears more robust than the deterministic one as it leads to less demanding identifiability conditions. View full abstract»

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  • Joint (3,k)-regular LDPC code and decoder/encoder design

    Page(s): 1065 - 1079
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB) |  | HTML iconHTML  

    Recently, low-density parity-check (LDPC) codes have attracted a lot of attention in the coding theory community. However, their real-world applications are still problematic mainly due to the lack of effective decoder/encoder hardware design approaches. In this paper, we present a joint (3,k)-regular LDPC code and decoder/encoder design technique to construct a class of (3,k)-regular LDPC codes that not only have very good error-correcting capability but also exactly fit to high-speed partly parallel decoder and low-complexity encoder implementations. We also develop two techniques to further modify this joint design scheme to achieve more flexible tradeoffs between decoder hardware complexity and decoding speed. View full abstract»

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  • Flipping structure: an efficient VLSI architecture for lifting-based discrete wavelet transform

    Page(s): 1080 - 1089
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (816 KB) |  | HTML iconHTML  

    In this paper, an efficient very large scale integration (VLSI) architecture, called flipping structure, is proposed for the lifting-based discrete wavelet transform. It can provide a variety of hardware implementations to improve and possibly minimize the critical path as well as the memory requirement of the lifting-based discrete wavelet transform by flipping conventional lifting structures. The precision issues are also analyzed. By case studies of the JPEG2000 default lossy (9,7) filter, an integer (9,7) filter, and the (6,10) filter, the efficiency of the proposed flipping structure is demonstrated. View full abstract»

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  • Efficient variable partitioning and scheduling for DSP processors with multiple memory modules

    Page(s): 1090 - 1099
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    Multiple on-chip memory modules are attractive to many high-performance digital signal processing (DSP) applications. This architectural feature supports higher memory bandwidth by allowing multiple data memory accesses to be executed in parallel. However, making effective use of multiple memory modules remains difficult. The performance gain in this kind of architecture strongly depends on variable partitioning and scheduling techniques. In this paper, we propose a graph model known as the variable independence graph (VIG) and algorithms to tackle the variable partitioning problem. Our results show that VIG is more effective than interference graph for solving variable partitioning problem. Then, we present a scheduling algorithm known as the rotation scheduling with variable repartition (RSVR) to improve the schedule lengths efficiently on a multiple memory module architecture. This algorithm adjusts the variable partitions during scheduling and generates a compact schedule based on retiming and software pipelining. The experimental results show that the average improvement on schedule lengths is 44.8% by using RSVR with VIG. We also propose a design space exploration algorithm using RSVR to find the minimum number of memory modules and functional units satisfying a schedule length requirement. The algorithm produces more feasible solutions with equal or fewer number of functional units compared with the method using interference graph. View full abstract»

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  • Signaling methods for multimedia steganography

    Page(s): 1100 - 1111
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB) |  | HTML iconHTML  

    Conventional communication methods employ a wide variety of signaling techniques that essentially map a bit sequence to a real-valued sequence (which is a representation of a point in the signal constellation). The real-valued sequence is in turn transmitted over a communications channel. However, communication techniques for the purpose of multimedia steganography or data hiding have to transmit the real-valued sequence corresponding to a point in the signal constellation superimposed on the original content (without affecting the fidelity of the original content noticeably). In this paper, we explore practical solutions for signaling methods for multimedia steganography. Data hiding is seen as a sophisticated signaling technique using a periodic signal constellation. We propose such a signaling method and present both theoretical and simulated evaluations of its performance in an additive noise scenario. The problem of optimal choice of the parameters for the proposed technique is also explored, and solutions are presented. View full abstract»

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  • On convergence of the NIC algorithm for subspace computation

    Page(s): 1112 - 1115
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    The "novel information criterion" (NIC) algorithm was developed by Miao and Hua in 1998 for fast adaptive computation of the principal subspace of a vector sequence. The NIC algorithm is as efficient computationally as the PAST method, which was devised by Yang in 1995, and also has an attractive orthonormal property. Although all available evidence suggests that the NIC algorithm converges to the desired solution for any fixed leakage factor between zero and one, a complete proof (or disproof) has not been found, except for an arbitrarily small leakage factor. This paper presents this long-standing open problem with a discussion of what is known so far. The results shown in this paper provide a new insight into the orthonormal property of the NIC algorithm at convergence. 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
Zhi-Quan (Tom) Luo
University of Minnesota