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Signal Processing, IEEE Transactions on

Issue 3 • Date March 1999

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

    Publication Year: 1999 , Page(s): 839 - 843
    Cited by:  Papers (4)
    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»

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  • A low-power phase-splitting adaptive equalizer for high bit-rate communication systems

    Publication Year: 1999 , Page(s): 911 - 915
    Cited by:  Papers (1)  |  Patents (1)
    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»

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  • DOA estimation of wideband sources using a harmonic source model and uniform linear array

    Publication Year: 1999 , Page(s): 619 - 629
    Cited by:  Papers (10)
    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»

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  • Performance analysis of wavelets in embedded zerotree-based lossless image coding schemes

    Publication Year: 1999 , Page(s): 884 - 889
    Cited by:  Papers (6)
    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»

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  • Resolution in time-frequency

    Publication Year: 1999 , Page(s): 783 - 788
    Cited by:  Papers (23)
    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»

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  • Blind equalization using least-squares lattice prediction

    Publication Year: 1999 , Page(s): 630 - 640
    Cited by:  Papers (9)
    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»

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  • Fractionally spaced equalization of linear polyphase channels and related blind techniques based on multichannel linear prediction

    Publication Year: 1999 , Page(s): 641 - 654
    Cited by:  Papers (54)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (560 KB)  

    We consider the problem of linear equalization of polyphase channels and its blind implementation. These channels may result from oversampling the single output of a transmission channel or/and by receiving multiple outputs of an antenna array. A number of previous contributions in the field of blind channel identification have shown that polyphase channels can be blindly identified using only second-order statistics (SOS) of the output. In this work, we are mostly interested in the blind linear equalization of these channels. After some elaboration on the specifics of the equalization problem for polyphase channels, we show how optimal settings of various well-known types of linear equalization structures can be obtained blindly using only the output's SOS by using multichannel linear prediction or related techniques View full abstract»

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  • A nonparametric phase estimation method for SIMO systems based on second-order and higher order statistics

    Publication Year: 1999 , Page(s): 843 - 847
    Cited by:  Papers (1)
    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»

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  • Undermodeled equalization: a characterization of stationary points for a family of blind criteria

    Publication Year: 1999 , Page(s): 760 - 770
    Cited by:  Papers (15)
    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»

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  • Mathematical programming algorithms for regression-based nonlinear filtering in RN

    Publication Year: 1999 , Page(s): 771 - 782
    Cited by:  Papers (8)
    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»

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  • B-spline design of maximally flat and prolate spheroidal-type FIR filters

    Publication Year: 1999 , Page(s): 701 - 716
    Cited by:  Papers (5)
    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»

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  • Initialization and inner product computations of wavelet transform by interpolatory subdivision scheme

    Publication Year: 1999 , Page(s): 876 - 880
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB)  

    The initialization of wavelet transforms and the inner product computations of wavelets with their derivatives are very important in many applications. In this correspondence, the interpolatory subdivision scheme (ISS) is proposed to solve these problems efficiently. We introduce a general procedure to compute the exact values of derivatives of the interpolatory fundamental function and then derive a fast recursive algorithm for the realization of the initialization and inner product evaluations. Error analysis of the algorithm and its comparison with other approaches are discussed. Numerical experiments demonstrate the high performance of the algorithm View full abstract»

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  • Weighted least-squares implementation of Cohen-Posch time-frequency distributions with specified conditional and joint moment constraints

    Publication Year: 1999 , Page(s): 893 - 900
    Cited by:  Papers (3)
    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»

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  • A function of time, frequency, lag, and Doppler

    Publication Year: 1999 , Page(s): 789 - 799
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (528 KB)  

    In signal processing, four functions of one variable are commonly used. They are the signal in time, the spectrum, the auto-correlation function of the signal, and the auto-correlation function of the spectrum. The variables of these functions are denoted, respectively, as time, frequency, lag, and Doppler. In time-frequency analysis, these functions of one variable are extended to quadratic functions of two variables. In this paper, we investigate a method for creating quartic functions of three of these variables as well as a quartic function of all four variables. These quartic functions provide a meaningful representation of the signal that goes beyond the well-known quadratic functions. The quartic functions are applied to the design of signal-adaptive kernels for the Cohen class and shown to provide improvements over previous methods View full abstract»

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  • Stochastic analysis of gradient adaptive identification of nonlinear systems with memory for Gaussian data and noisy input and output measurements

    Publication Year: 1999 , Page(s): 675 - 689
    Cited by:  Papers (29)
    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»

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  • Evolutionary spectrum estimation by positivity constrained deconvolution

    Publication Year: 1999 , Page(s): 889 - 893
    Cited by:  Papers (3)
    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»

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  • Application of cumulants to array signal processing .V. Sensitivity issues

    Publication Year: 1999 , Page(s): 746 - 759
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB)  

    For pt.IV see ibid., vol.45, p.2265-76 (1997). Virtual-ESPRIT (VESPA) imposes a slight constraint on the array, i.e., only a pair of identical sensors are required. We follow the classical procedure to define the sensitivity of VESPA with respect to each model parameter and derive closed forms for the sensitivity formulas. We justify our derivations by comparing the theoretical formulas with the results from Monte Carlo simulations. Additionally, we demonstrate, by simulations, that VESPA is more robust to model mismatches than ESPRIT in most situations View full abstract»

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  • An effective memory addressing scheme for FFT processors

    Publication Year: 1999 , Page(s): 907 - 911
    Cited by:  Papers (47)  |  Patents (3)
    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»

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  • Performance metrics for windows used in real-time DFT-based multiple-tone frequency excision

    Publication Year: 1999 , Page(s): 800 - 812
    Cited by:  Papers (6)  |  Patents (2)
    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»

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  • An adaptive noise canceller with low signal distortion for speech codecs

    Publication Year: 1999 , Page(s): 665 - 674
    Cited by:  Papers (20)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (412 KB)  

    This paper proposes an adaptive noise canceller (ANC) with low signal distortion for speech codecs. The proposed ANC has two adaptive filters: a main filter (MF) and a subfilter (SF). The signal-to-noise ratio (SNR) of input signals is estimated using the SF. To reduce signal distortion in the output signal of the ANC, a step size for coefficient update in the MF is controlled according to the estimated SNR. Computer simulation results using speech and diesel engine noise recorded in a special-purpose vehicle show that the proposed ANC reduces signal distortion in the output signal by up to 15 dB compared with a conventional ANC. Results of subjective listening tests show that the mean opinion scores (MOSs) for the proposed ANC with and without a speech codec are one point higher than the scores for the conventional ANC View full abstract»

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  • A new approach to subband adaptive filtering

    Publication Year: 1999 , Page(s): 655 - 664
    Cited by:  Papers (52)
    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»

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  • A novel kurtosis driven variable step-size adaptive algorithm

    Publication Year: 1999 , Page(s): 864 - 872
    Cited by:  Papers (34)  |  Patents (1)
    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»

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  • An LMS adaptive second-order Volterra filter with a zeroth-order term: steady-state performance analysis in a time-varying environment

    Publication Year: 1999 , Page(s): 872 - 876
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB)  

    This article studies the steady-state performance of the least mean square (LMS) adaptive second-order Volterra filter (SOVF) with a zeroth-order term for Gaussian inputs. The mean-square-error (MSE) criterion is evaluated first. Then, SOV LMS algorithm-based updating equations are derived. Next, the steady-state performance of the recursions is analyzed for a random walk model for the unknown system parameters, and the steady-state excess MSE is evaluated. Finally, the theoretical performance predictions are shown to be in good agreement with simulation results, especially for small step sizes View full abstract»

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  • Minimum-noise-variance beamformer with an electromagnetic vector sensor

    Publication Year: 1999 , Page(s): 601 - 618
    Cited by:  Papers (19)
    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»

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  • A refined fast 2-D discrete cosine transform algorithm

    Publication Year: 1999 , Page(s): 904 - 907
    Cited by:  Papers (9)
    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»

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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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Editor-in-Chief
Sergios Theodoridis
University of Athens