By Topic

Signal Processing, IEEE Transactions on

Issue 3 • Date March 1999

Filter Results

Displaying Results 1 - 25 of 35
  • Lag-windowing and multiple-data-windowing are roughly equivalent for smooth spectrum estimation

    Page(s): 839 - 843
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (187 KB)  

    There is no fundamental difference between lag-windowing a correlation sequence and multiple-windowing a data sequence when the objective is to reduce the mean-squared error of a spectrum estimator. By analyzing the approximate low-rank factorization of a bandlimiting Toeplitz operator, we find that lag-windowed (or spectrally smoothed) spectrum estimators have multiple-data-windowed implementations. This makes the Blackman-Tukey-Grenander-Rosenblatt spectrogram equivalent to the Thomson spectrum estimator (and vice-versa), meaning BTGR spectrograms may be implemented in a multichannel filterbank version of the Thomson estimator. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A refined fast 2-D discrete cosine transform algorithm

    Page(s): 904 - 907
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB)  

    An index permutation-based fast two-dimensional discrete cosine transform (2-D DCT) algorithm is presented. It is shown that the N×N 2-D DCT, where N=2m, can be computed using only N 1-D DCTs and some post additions View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Undermodeled equalization: a characterization of stationary points for a family of blind criteria

    Page(s): 760 - 770
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (480 KB)  

    We attack specific problems related to equalizer performance in undermodeled cases in which assumptions of perfect equalizability are dismissed in favor of a more realistic situation in which no equalizer setting may achieve perfect channel equalization. We derive a characterization of candidate convergent points for a family of blind criteria which appeal, tacitly or wittingly, to maximizing the ratio of different sequence norms of the combined channel-equalizer impulse response. This may be accomplished in a practical implementation by using equalizer output cumulants of different orders. The popular Godard and Shalvi-Weinstein schemes are accommodated at one extreme of the family of criteria. We also show that each maximum at the other extreme of the family, involving progressively higher order output cumulants, yields, precisely, a Wiener response. This suggests that blind algorithms using progressively higher order statistics may converge more closely to a Wiener response than those using more modest order statistics. We show, moreover, that the superexponential family of algorithms is also included and establish a convergence proof for undermodeled cases that appeals to no approximation. Finally, some apparently novel bounds on attainable open-eye measures in undermodeled cases are also derived View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Evolutionary spectrum estimation by positivity constrained deconvolution

    Page(s): 889 - 893
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (212 KB)  

    We present a deconvolution technique to obtain the evolutionary spectrum (ES) of nonstationary signals by deconvolving the blurring effects of the time-frequency distribution (TFD) kernel from bilinear TFDs. The resulting spectrum is non-negative and has desirable properties such as higher resolution and higher concentration in time frequency. The new technique is computationally more efficient compared with the previously proposed entropy-based deconvolution technique, and, unlike the entropy method, it is not restricted to deconvolution of spectrograms with Gaussian windows. This makes the method applicable to deconvolving many of the bilinear time-frequency distributions View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Implementation issues of the two-level residue number system with pairs of conjugate moduli

    Page(s): 826 - 838
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB)  

    One of the most important considerations when designing residue number systems (RNSs) is the choice of the moduli set; this is due to the fact that the dynamic range of the system, its speed, as well as its hardware complexity, depend on both the forms as well as the number of moduli chosen; In this paper, a new class of multimoduli RNSs based on sets of forms {2n(1)-1, 2n(1)+1, 2n2-1, 2n(2)+1, ···, 2n(L)-1, 2n(L)+1} is presented. The moduli 2n(i)-1 and 2 n(i)+1 are called conjugates of each other. The new RNSs that rely on pairs of conjugate moduli result in hardware-efficient two-level implementations for the weighted-to-RNS and RNS-to-weighted conversions, achieve very large dynamic ranges, and imply fast and efficient RNS processing. When compared with conventional systems of the same number of moduli and the same dynamic range, the proposed new systems offer the following benefits: (1) hardware savings of 25 to 40% for the weighted-to-RNS conversion and (2) a reduction of over 80% in the complexity of the final Chinese remainder theorem (CRT) involved in the RNS-to-weighted conversion. Thus, significant compromises between large dynamic ranges, fast internal processing, and low complexity are achieved by the new systems View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A low-power phase-splitting adaptive equalizer for high bit-rate communication systems

    Page(s): 911 - 915
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB)  

    A low-power architecture for a phase-splitting passband equalizer (PSPE) is proposed for a transceiver in this correspondence. The Hilbert relationship between the in-phase and quadrature-phase equalizers in the PSPE is exploited to develop the proposed architecture. It is shown via analysis and simulations that in a 51.84-Mb/s ATM-LAN environment, the proposed receiver results in (1) a net saving in power if the length of the Hilbert filter is less than 130, and (2) a saving of up to 20% can be achieved with a degradation in signal-to-noise ratio of less than 0.5 dB View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Exploiting input cyclostationarity for blind channel identification in OFDM systems

    Page(s): 848 - 856
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    Transmitter-induced cyclostationarity has been explored previously as an alternative to fractional sampling and antenna array methods for blind identification of FIR communication channels. An interesting application of these ideas is in OFDM systems, which induce cyclostationarity due to the cyclic prefix. We develop a novel subspace approach for blind channel identification using cyclic correlations at the OFDM receiver. Even channels with equispaced unit circle zeros are identifiable in the presence of any nonzero length cyclic prefix with adequate block length. Simulations of the proposed channel estimator along with its performance in OFDM systems combined with impulse response shortening and Reed-Solomon coding are presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Performance metrics for windows used in real-time DFT-based multiple-tone frequency excision

    Page(s): 800 - 812
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (456 KB)  

    The capability of direct-sequence spread-spectrum receivers to reject narrowband interference can be significantly improved by eliminating narrowband energy in the received signal through a real-time discrete Fourier transform (RT-DFT) process. However, the loss in received signal strength due to this frequency excision process can be significant. In this paper, we present a theoretical framework for evaluating the performance of alternative combinations of time weighting functions (windows), fractions of overlap in overlap-and-add architectures, and frequency-domain mapping algorithms. The sensitivity loss due to time weighting is presented for variable overlaps and several different windows. A set of window metrics is defined that provides a means of calculating distortion losses for an arbitrary number of interfering tones with uniformly distributed center frequencies. Theoretical results are confirmed by simulation. These results can be used to compare sensitivities of alternative RT-DFT frequency excision direct-sequence spread-spectrum systems and to calculate the standoff range of a finite number of in-band tone emitters View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An effective memory addressing scheme for FFT processors

    Page(s): 907 - 911
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    The memory organization of FFT processors is considered. The new memory addressing assignment allows simultaneous access to all the data needed for butterfly calculations. The advantage of this memory addressing scheme lies in the fact that it reduces the delay of address generation nearly by half compared to existing ones View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Blind equalization using least-squares lattice prediction

    Page(s): 630 - 640
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB)  

    Second-order statistics of the received signal can be used to equalize a communication channel without knowledge of the transmitted sequence. Blind zero-forcing (ZF) and minimum mean-square error (MMSE) equalization can be achieved with linear prediction error filtering. The equivalence with the equalizers derived by Giannakis and Halford (see ibid., vol.45, p.2277-92, 1997) is shown, and adaptive predictors that result in a lattice filtering structure are applied. The required channel coefficient vector is obtained with adaptive eigen-pair tracking. Either forward or backward prediction errors can be used. The performance of the blind equalizer is examined by simulations. The MMSE of the optimum FSE is approached, and the algorithm exhibits robustness to channels with common subchannel zeros View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multichannel linear and quadratic adaptive filtering based on the Chandrasekhar fast algorithm

    Page(s): 860 - 864
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (188 KB)  

    A new fast algorithm for multichannel linear and quadratic adaptive filtering using the Chandrasekhar equations is presented. Based on the shift-invariance property, the multichannel linear model could be described by a time-invariant state-space model to which we apply the Chandrasekhar factorization technique, which provides interesting numerical properties. Furthermore, a new method for nonlinear filtering is given where the multichannel Chandrasekhar algorithm is applied on the second-order Volterra (SOV) filter after suitable transformations View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Zolotarev polynomials and optimal FIR filters

    Page(s): 717 - 730
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (728 KB)  

    The algebraic form of Zolotarev polynomials refraining from their parametric representation is introduced. A recursive algorithm providing the coefficients for a Zolotarev polynomial of an arbitrary order is obtained from a linear differential equation developed for this purpose. The corresponding narrowband, notch, and complementary pair FIR filters are optimal in the Chebyshev sense. A recursion giving an explicit access to the impulse response coefficients is also presented. Some design examples are included to demonstrate the efficiency of the presented approach View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Performance analysis of wavelets in embedded zerotree-based lossless image coding schemes

    Page(s): 884 - 889
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    In this correspondence, we present a modification to the scanning approach in the set partitioning algorithm proposed by Said and Pearlman (1996) to exploit the correlation in a local neighborhood. The wavelet filters are characterized based on the wavelet coefficients obtained after the wavelet transform. Two new criteria are proposed for evaluating the performance of wavelets in lossless image compression applications: cumulative zerotree count and monotone spectral ordering of subbands produced after wavelet transform in a multiresolution scheme. Several wavelet filters are evaluated to test the evaluation criteria. The experimental results are presented to justify the proposed performance criteria View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • B-spline design of maximally flat and prolate spheroidal-type FIR filters

    Page(s): 701 - 716
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (540 KB)  

    A digital FIR filter is described that offers excellent passband and stopband characteristics for general applications. Design formulae include parameters that adjust the magnitude response from one having characteristics like the maximally flat designs of Hermann (1971) and Kaiser (1975, 1979) to one having characteristics like the minimum-sidelobe energy approximations of Kaiser and Saramaki (1989). The impulse response coefficients are more straightforward to obtain than these filter designs while offering preferable response characteristics in many instances. Unlike FIR filters designed by window- or frequency-sampling methods, the filter coefficients are determined from the inverse Fourier transform in closed form once B-splines have been used to replace sharp transition edges of the magnitude response. Although the filters are developed in the frequency domain, a convergence window is identified in the convolution series and compared with windows of popular FIR filters. By means of example, adjustment of the transitional parameter is shown to produce a filter response that rivals the stopband attenuation and transition width of prolate spheroidal designs. The design technique is extended to create additional transitional filters from prototype window functions, such as the transitional Hann window filter. The filters are particularly suitable for precision filtering and reconstruction of sampled physiologic and acoustic signals common to the health sciences but will also be useful in other applications requiring low passband and stopband errors View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Resolution in time-frequency

    Page(s): 783 - 788
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (260 KB)  

    We introduce a new measure Hp that is related to the Heisenberg uncertainty principle. The measure predicts the compactness of discrete-time signal descriptions in the sample-frequency phase plane. We conjecture a lower limit on the compaction in the phase plane and show that discretized Gaussians may not provide the most compact basis View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • DOA estimation of wideband sources using a harmonic source model and uniform linear array

    Page(s): 619 - 629
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (432 KB)  

    We consider the problem of estimation of the DOAs of multiple wideband sources incident on a uniform linear array (ULA) in the presence of spatially and temporally white Gaussian noise (WGN). The approach presented builds up on the IQML algorithm suggested by Bresler and Macovski (1986) for the case of narrowband DOA estimation. It is shown that the concept of an ARMA model for the observed data vector for the narrowband case can be generalized to model an appropriately stacked, space-time data vector obtained by combining the space-time samples. The coefficients of the corresponding 2-D predictor polynomial can be used to represent the null subspace of the wideband array steering matrix, and rooting of the polynomial at each frequency, separately, gives the DOA estimates. These separate estimates at multiple frequencies are combined into a single DOA estimate in a least squares sense. This leads to the formulation of an IQML like procedure for the spatial parameter estimation of wideband sources. Like its narrowband counterpart, the proposed approach is applicable to both noncoherent and coherent sources. The performance of the proposed method is studied via extensive computer simulations and by comparison with the Cramer-Rao bounds View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A new approach to subband adaptive filtering

    Page(s): 655 - 664
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (428 KB)  

    Subband adaptive filtering has attracted much attention lately. In this paper, we propose a new structure and a new formulation for adapting the filter coefficients. This structure is based on polyphase decomposition of the filter to be adapted and is independent of the type of filter banks used in the subband decomposition. The new formulation yields improved convergence rate when the LMS algorithm is used for coefficient adaptation. As we increase the number of bands in the filter, the convergence rate increases and approaches the rate that can be obtained with a flat input spectrum. The computational complexity of the proposed scheme is nearly the same as that of the fullband approach. Simulation results are included to demonstrate the efficacy of the new approach View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stochastic analysis of gradient adaptive identification of nonlinear systems with memory for Gaussian data and noisy input and output measurements

    Page(s): 675 - 689
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (888 KB)  

    This paper investigates the statistical behavior of two gradient search adaptive algorithms for identifying an unknown nonlinear system comprised of a discrete-time linear system H followed by a zero-memory nonlinearity g(·). The input and output of the unknown system are corrupted by additive independent noises. Gaussian models are used for all inputs. Two competing adaptation schemes are analyzed. The first is a sequential adaptation scheme where the LMS algorithm is first used to estimate the linear portion of the unknown system. The LMS algorithm is able to identify the linear portion of the unknown system to within a scale factor. The weights are then frozen at the end of the first adaptation phase. Recursions are derived for the mean and fluctuation behavior of the LMS algorithm, which are in excellent agreement with Monte Carlo simulations. When the nonlinearity is modeled by a scaled error function, the second part of the sequential gradient identification scheme is shown to correctly learn the scale factor and the error function scale factor. Mean recursions for the scale factors show good agreement with Monte Carlo simulations. For slow learning, the stationary points of the gradient algorithm closely agree with the stationary points of the theoretical recursions. The second adaptive scheme simultaneously learns both the linear and nonlinear portions of the unknown channel. The mean recursions for the linear and nonlinear portions show good agreement with Monte Carlo simulations for slow learning. The stationary points of the gradient algorithm also agree with the stationary points of the theoretical recursions View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Bootstrapping bispectra: an application to testing for departure from Gaussianity of stationary signals

    Page(s): 880 - 884
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (180 KB)  

    We propose a bootstrap version of a bispectrum-based test for departure from Gaussianity that achieves high power while maintaining the level of significance, even for small sample sizes. The proposed procedure can be also used to set confidence bands for a measure of the bicoherence of stationary random signals View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mathematical programming algorithms for regression-based nonlinear filtering in RN

    Page(s): 771 - 782
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (396 KB)  

    This paper is concerned with regression under a “sum” of partial order constraints. Examples include locally monotonic, piecewise monotonic, runlength constrained, and unimodal and oligomodal regression. These are of interest not only in nonlinear filtering but also in density estimation and chromatographic analysis. It is shown that under a least absolute error criterion, these problems can be transformed into appropriate finite problems, which can then be efficiently solved via dynamic programming techniques. Although the result does not carry over to least squares regression, hybrid programming algorithms can be developed to solve least squares counterparts of certain problems in the class View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A nonparametric phase estimation method for SIMO systems based on second-order and higher order statistics

    Page(s): 843 - 847
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (164 KB)  

    We present a nonparametric phase estimation algorithm for linear single-input multiple-output (SIMO) channels. Given an unknown stationary input signal with known statistics, our approach is to obtain the joint minimum mean square phase estimation based on the polyspectra and the cross-spectra of the SIMO channel outputs. By utilizing both higher order and second-order statistics of the channel outputs, our approach is shown to be more accurate and reliable than methods based on higher order statistics alone. It can be applied to SIMO channels with common zeros View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fast DHT algorithms for length N=q*2m

    Page(s): 900 - 903
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (164 KB)  

    This article presents an improved split-radix algorithm that can flexibly compute the discrete Hartley transforms (DHT) of length-q*2m where q is an odd integer. Comparisons with previously reported algorithms show that savings on the number of arithmetic operations can be made. Furthermore, a wider range of choices on different DHT lengths is naturally provided View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Minimum-noise-variance beamformer with an electromagnetic vector sensor

    Page(s): 601 - 618
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (992 KB)  

    We study the performance of the minimum-noise-variance beamformer employing a single electromagnetic (EM) vector sensor that is capable of measuring the complete electric and magnetic fields induced by EM signals at one point. Two types of signals are considered: one carries a single message, and the other carries two independent messages simultaneously. The state of polarization of the interference under consideration ranges from completely polarized to unpolarized. We first obtain explicit expressions for the signal to interference-plus-noise ratio (SINR) in terms of the parameters of the signal, interference, and noise. Then, we discuss some physical implications associated with the SINR expressions. These expressions provide a basis for effective interference suppression as well as generation of dual-message signals of which the two message signals have minimum interference effect on one another. We also analyze the characteristics of the main-lobe and side-lobe of the beampattern of an EM vector sensor and compare them with other types of sensor arrays View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Weighted least-squares implementation of Cohen-Posch time-frequency distributions with specified conditional and joint moment constraints

    Page(s): 893 - 900
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB)  

    A positivity constrained iterative weighted least-squares (WLS) method for constructing non-negative joint time-frequency distributions (i.e., Cohen-Posch (1985) TFDs) satisfying marginal, joint moment, conditional moment, and generalized marginal constraints, is developed. The new algorithm solves the “leakage” problem of the least-squares approach and is computationally faster. It is also more computationally efficient than the MCE implementation of these constraints developed by Loughlin, Pitton, and Atlas (1994) View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A novel kurtosis driven variable step-size adaptive algorithm

    Page(s): 864 - 872
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (256 KB)  

    A new variable step-size LMS filter is introduced. The time-varying step-size sequence is adjusted, utilizing the kurtosis of the estimation error, therefore reducing performance degradation due to the existence of strong noise. The convergence properties of the algorithm are analyzed, and an adaptive kurtosis estimator that takes into account noise statistics and optimally adapts itself is also presented. Simulation results confirm the algorithm's improved performance and flexibility View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Zhi-Quan (Tom) Luo
University of Minnesota