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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 3 • Date March 1987

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Displaying Results 1 - 21 of 21
  • [Front cover and table of contents]

    Publication Year: 1987 , Page(s): 0
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    Freely Available from IEEE
  • Supplement to "On two-dimensional polyphase filter banks"

    Publication Year: 1987 , Page(s): 403 - 404
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    First Page of the Article
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  • [Back cover]

    Publication Year: 1987 , Page(s): c4
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    Freely Available from IEEE
  • A new filter bank theory for time-frequency representation

    Publication Year: 1987 , Page(s): 314 - 327
    Cited by:  Papers (62)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1568 KB)  

    This paper presents a new formalism for the description of analysis/synthesis systems based on filter banks. Although this work was done in the context of speech coding systems, the results apply to a far broader class of problems. This new formalism has three specific advantages. First, it allows for the description of many different techniques and approaches with one unifying theory. Second, it enables the decoupling of the effects of the various distorting elements in the system design process, allowing each to be addressed separately. Finally, it allows for the relatively simple invention of entirely new techniques in such a way that the relationship of the new approaches to previously developed techniques is always clear. View full abstract»

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  • Further results in Walsh domain filtering

    Publication Year: 1987 , Page(s): 394 - 397
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB)  

    Zarowski and Yunik [1] demonstrated that an FIR filter can be realized with fewer multiplications in the fast Walsh transform (FWT) domain than in the fast Fourier transform (FFT) domain for some transform lengths. This correspondence investigates the symmetry and sparseness of the Walsh gain matrices. An efficient sparse matrix algorithm is used to calculate the Walsh gain matrix. View full abstract»

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  • A hybrid Hadamard LPC scheme for picture coding

    Publication Year: 1987 , Page(s): 391 - 394
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    A transform-LPC hybrid system for real-time coding of picture data has been presented. The LPC has been made adaptive by using a correlation cancellation loop. Three different schemes for coding and reconstructing the transform components have been presented and their relative performances have been compared. The MSE and SNR are seen to be comparable to previous work on transform-DPCM hybrid schemes. View full abstract»

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  • On the shift property of DCT's and DST's

    Publication Year: 1987 , Page(s): 404 - 406
    Cited by:  Papers (26)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB)  

    The relationship between the family of DCT's and DST's of original sequence and shifted sequences is developed. While these properties are not as simple as the case for the DFT, they are still useful for processing long streams of data sequences where time-varying filtering is required. View full abstract»

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  • Array shape calibration using sources in unknown locations--Part I: Far-field sources

    Publication Year: 1987 , Page(s): 286 - 299
    Cited by:  Papers (160)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1296 KB)  

    This paper deals with source localization using a two-dimensional array of sensors whose locations are not known precisely. If only a single source is observed, uncertainties in sensor location increase errors in source bearing and range by an amount which is independent of signal-to-noise ratio and which can easily dominate over-all localization accuracy. Major performance gains could therefore result from successful calibration of array geometry. The paper derives Cramer-Rao bounds on calibration and source location accuracies achievable with far-field sources whose bearings are not initially known. The sources are assumed to radiate Gaussian noise and to be spectrally disjoint of each other. When the location of one sensor and the direction to a second sensor is known, three noncollinear sources are sufficient to calibrate sensor positions with errors which decrease to zero as calibrating source strength or time-bandwidth products tend to infinity. The sole exception to this statement is a nominally linear array for which such calibration is not possible. When one sensor location is known but no directional reference is available, three noncollinear sources can determine array shape, but there remains a residual error in angular orientation which is irremovable by the calibration procedure. When no sensor locations are known a priori, one adds to the residual error in rotation a translational component. In the far field, the latter should be unimportant. In addition to the asymptotic results, Cramer-Rao bounds are computed for finite signal-to-noise ratios and observation times. One finds that calibration permits significant reductions in localization errors for parameter values well within the practical range. View full abstract»

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  • Spatial/Spectral filtering with linearly constrained minimum variance beamformers

    Publication Year: 1987 , Page(s): 249 - 266
    Cited by:  Papers (125)  |  Patents (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1832 KB)  

    In this paper, orthogonal low-dimension models for broad-band sources, as observed by an array/delay-line structure, are developed. The models are termed broad-band source representation spaces, and are subspaces of the observation space. They are generated from eigenstructures of source sample covariance matrices and represent sources efficiently in the 2nd-order statistical sense. For a single broad-band source, propagating in a pure delay environment and observed with an isotropic array, an accurate indication of the model dimension is derived which is independent on the array configuration, being a function of the observed source time-bandwidth product only. Using these representations, procedures are described for controlling the spatial and spectral response of linearly constrained minimum variance broad-band array/beamformers. The procedures employ linear constraints to control complex gain characteristics, over selected bands of frequency, for multiple points of 3-D regions of source locations and do not require the use of steering delays. The constraints are derived from source representation spaces and are termed eigenvector constraints. Simulations are presented which illustrate the effectiveness of the new linear constraints. View full abstract»

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  • Two-channel likelihood detectors for arbitrary linear channel distortion

    Publication Year: 1987 , Page(s): 267 - 273
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB)  

    This paper derives likelihood and generalized likelihood detection test statistics for a set of two-channel problems. This set includes additive Gaussian and non-Gaussian noise, known signals, signals with unknown deterministic parameters, signals with unknown statistical parameters, and signals completely unknown. The set also includes arbitrary linear channel distortion, which is a generalization of time delay, frequency shift, and multipath. Simple expressions are obtained for the test statistic in the weak signal limit for additive non-Gaussian noise. The ambiguity function is derived under the assumption of white Gaussian noise with the signal completely unknown. Generalizations of the ambiguity function are derived and are used to construct detection statistics for other signal problems. View full abstract»

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  • Estimation of close sinusoids in colored noise and model discrimination

    Publication Year: 1987 , Page(s): 328 - 337
    Cited by:  Papers (35)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1144 KB)  

    This paper considers the estimation of the two close dominant frequencies in the signal when it is known a priori that the observation is a sum of two close sinusoids and an additive colored noise whose spectral density is unknown. Earlier attempts have assumed the additive noise to be independent. Next we develop decision rules for checking whether the observed signal has only one sinusoid or two close sinusoids. All of the earlier studies assumed that there are two close sinusoids in the signal. Another model discrimination problem considered is the determination of the causal structure of the observed periodicity. A rule is given to test whether the observation comes from a sinusoid plus additive noise, possible colored, or the observation comes from a stationary autoregressive model. We also present a numerical study showing the efficacy of the robust estimation procedure for estimating the two frequencies and the decision rules for checking the number of dominant frequencies and the causal mechanism. Finally, we compare the proposed method to well-known methods used for two close sinusoids in white noise. View full abstract»

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  • A unified approach to nonparametric spectrum estimation algorithms

    Publication Year: 1987 , Page(s): 338 - 349
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1392 KB)  

    Different approaches to spectrum estimation can be broadly classified as parametric and nonparametric methods. In the parametric techniques, an underlying model is assumed in the formulation of the spectrum estimation problem and one estimates the parameters of the model. For nonparametric methods, no such model is assumed. In this paper, several nonparametric spectrum estimation algorithms are brought under a unified framework by the introduction of a generalized nonparametric spectrum estimation algorithm. A four-stage approach is employed. It contains as special cases the Blackman-Tukey algorithm, the weighted, overlapped segment averaging (WOSA) method, the lag-reshape approach, Rader's algorithm, and the short-time unbiased spectrum estimation (STUSE) algorithm. The framework proposed in the paper is more general than the one recently proposed by Nuttall and Carter. Theoretical expressions for the spectrum estimation variance of the generalized algorithm are derived, and then verified via simulation example. Also, several nonparametric approaches for obtaining unbiased spectrum estimates are discussed and compared. Finally we conclude the paper with a brief discussion of the applicability and usefulness of several methods in specific situations. View full abstract»

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  • Maximum-likelihood estimation of time-varying delay--Part I

    Publication Year: 1987 , Page(s): 300 - 313
    Cited by:  Papers (29)
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    This paper presents, for the first time, the exact theoretical solution to the problem of maximum-likelihood (ML) estimation of time-varying delay d(t) between a random signal s(t) received at one point in the presence of uncorrelated noise, and the time-delayed, scaled version αs(t - d(t)) of that signal received at another point in the presence of uncorrelated noise. The signal is modeled as a sample function of a nonstationary Gaussian random process and the observation interval is arbitrary. The analysis of this paper represents a generalization of that of Knapp and Carter [1], who derived the ML estimator for the case that the delay is constant, d(t) = d0, the signal process is stationary, and the received processes are observed over the infinite interval (-∞, +∞). We show that the ML estimator of d(t) can be implemented in any of four canonical forms which, in general, are time-varying systems. We also show that our results reduce to a generalized cross correlator for the special case treated in [1]. View full abstract»

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  • Multidimensional cyclic convolution algorithms with minimal multiplicative complexity

    Publication Year: 1987 , Page(s): 384 - 390
    Cited by:  Papers (3)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (664 KB)  

    This paper presents novel multidimensional cyclic convolution algorithms which achieve the theoretically minimum number of multiplications. The proposed algorithms are compared to the well-known and used polynomial transform and split nesting convolution algorithms. View full abstract»

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  • Passive range estimation of an underwater maneuvering target

    Publication Year: 1987 , Page(s): 274 - 285
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1056 KB)  

    This paper examines the problem of adaptively tracking, in the horizontal ocean plane, an underwater maneuvering target using passive, time delay measurements. The target is free to make large scale random changes in velocity and bearing at times that are unknown to the observer. Tracking is accomplished by utilizing the basic linearized polar or "spherical" model of target and observer motion previously developed for radar tracking of airborne maneuvering vehicles[1]. The addition of a nonlinear system block to the tracking system leads to a partial decoupling of both bearing and polar range estimators which not only reduces computational burden, but also significantly reduces any tendency toward tracking divergence. A modified method to obtain closed-form expressions for the measurement error statistics is presented which replaces conventional extensive off-line simulation procedures. Finally, test results are shown which validate the elimination of all extended Kalman filters in the measurement processing. This makes the passive tracking system very "robust" with respect to convergence characteristics in the presence of adverse target maneuvers. View full abstract»

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  • Adaptive restoration of images with speckle

    Publication Year: 1987 , Page(s): 373 - 383
    Cited by:  Papers (163)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2080 KB)  

    Speckle is a granular noise that inherently exists in all types of coherent imaging systems. The presence of speckle in an image reduces the resolution of the image and the detectability of the target. Many speckle reduction algorithms assume speckle noise is multiplicative. We instead model the speckle according to the exact physical process of coherent image formation. Thus, the model includes signal-dependent effects and accurately represents the higher order statistical properties of speckle that are important to the restoration procedure. Various adaptive restoration filters for intensity speckle images are derived based on different model assumptions and a nonstationary image model. These filters respond adaptively to the signal-dependent speckle noise and the nonstationary statistics of the original image. View full abstract»

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  • A comparison of two source azimuth estimation schemes

    Publication Year: 1987 , Page(s): 402 - 403
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    This correspondence compares two azimuth estimation schemes via a simulation, based on the estimated values and the corresponding variances. The comparison is an empirical one, and no claims are made about either scheme reaching the Cramer-Rao lower bound. Both of the schemes operate on single station data as opposed to standard techniques developed for array data. View full abstract»

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  • Estimation of probabilities from sparse data for the language model component of a speech recognizer

    Publication Year: 1987 , Page(s): 400 - 401
    Cited by:  Papers (181)  |  Patents (47)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB)  

    The description of a novel type of m-gram language model is given. The model offers, via a nonlinear recursive procedure, a computation and space efficient solution to the problem of estimating probabilities from sparse data. This solution compares favorably to other proposed methods. While the method has been developed for and successfully implemented in the IBM Real Time Speech Recognizers, its generality makes it applicable in other areas where the problem of estimating probabilities from sparse data arises. View full abstract»

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  • A theory of multirate filter banks

    Publication Year: 1987 , Page(s): 356 - 372
    Cited by:  Papers (205)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1776 KB)  

    Multirate filter banks produce multiple output signals by filtering and subsampling a single input signal, or conversely, generate a single output by upsampling and interpolating multiple inputs. Two of their main applications are subband coders for speech processing and transmultiplexers for telecommunications. Below, we derive a theoretical framework for the analysis, synthesis, and computational complexity of multirate filter banks. The use of matrix notation leads to basic results derived from properties of linear algebra. Using rank and determinant of filter matrices, it is shown how to obtain aliasing/ crosstalk-free reconstruction, and when perfect reconstruction is possible. The synthesis of filters for filter banks is also explored, three design methods are presented, and finally, the computational complexity is considered. View full abstract»

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  • Adaptive hybrid balancing based on a novel recursive estimation algorithm and spectral analysis

    Publication Year: 1987 , Page(s): 397 - 399
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB)  

    This correspondence presents an investigation of a recursive estimation algorithm [1] (whose updates of estimates are information dependent) as applied to adaptive hybrid balancing in telephony. When compared to conventional schemes such as recursive least-squares (RLS) and stochastic gradient (SG) methods [2]-[7], the algorithm is superior in terms of the level of echo return loss and computational requirements. View full abstract»

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  • Rank reduction for modeling stationary signals

    Publication Year: 1987 , Page(s): 350 - 355
    Cited by:  Papers (79)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB)  

    Rank reduction is developed as a general principle for trading off model bias and model variance in the analysis and synthesis of signals. The principle is applied to three basic problems: stationary time series modeling, stationary time series whitening, and vector quantization. Each problem brings its own surprises and insights. View full abstract»

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Aims & Scope

This Transactions ceased production in 1990. The current retitled publication is IEEE Transactions on Signal Processing.

Full Aims & Scope