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Signal Processing, IEEE Transactions on

Issue 3 • Date March 1992

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Displaying Results 1 - 25 of 28
  • Comments on "Fourier analysis and signal processing by use of the Mobius inversion formula" (by I.S. Reed) et al

    Publication Year: 1992
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (73 KB)  

    A method of Fourier analysis based on the number-theoretic Mobius inversion was recently developed by Reed et al. (see ibid., vol.38, no.3, p.458, 1990). A few corrections needed in its proof of theorems and equations are given here.<> View full abstract»

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  • Multiple window based minimum variance spectrum estimation for multidimensional random fields

    Publication Year: 1992 , Page(s): 578 - 589
    Cited by:  Papers (6)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (940 KB)  

    Spectrum analysis is viewed as the problem of estimating the power of a process contained within narrow bands. This view leads naturally to consideration of filter-based methods for estimating spectra. Multiple window-based estimators where the power in a band is estimated as the average of the powers estimated at the outputs of multiple filters are considered. The filters are designed using a linearly constrained minimum variance criterion commonly employed in adaptive beamforming. This results in filters that automatically adjust their sidelobes to minimize leakage of energy from outside the band of interest. Expressions for the bias and variance of the power estimates are derived assuming the sample covariance matrix estimate is used to estimate the data covariance matrix and that the data are independent and identically Gaussian distributed. These expressions lead to the definition of a performance factor that indicates the degree of variance reduction obtained via multiple window processing. A technique for obtaining increased suppression of energy leaking through the filter sidelobes at the expense of the response fidelity to energy in the band is presented. Simulations are presented to illustrate the effectiveness of the technique View full abstract»

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  • Nonstationary autoregressive modeling of object contours

    Publication Year: 1992 , Page(s): 660 - 675
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1208 KB)  

    A spatially variant circular autoregressive (SVCAR) model is introduced for the analysis and classification of closed shape boundaries. The model represents a closed shape boundary sequence as the output of a nonstationary all-pole linear system (driven by white noise) whose coefficient's spatial evolution can be expressed as a truncated function expansion. Features derived from the SVCAR model are shown to be invariant to shape scaling, rotation, and translation. A shape-matching algorithm is developed to optimally adjust the SVCAR model coefficients for changes in contour sequence starting point. Laboratory experiments involving object sets representative of industrial, military, and geographic shapes are presented. Superior classification results are demonstrated View full abstract»

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  • Shape invariant time-scale and pitch modification of speech

    Publication Year: 1992 , Page(s): 497 - 510
    Cited by:  Papers (61)  |  Patents (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1200 KB)  

    The simplified linear model of speech production predicts that when the rate of articulation is changed, the resulting waveform takes on the appearance of the original, except for a change in the time scale. A time-scale modification system that preserves this shape-invariance property during voicing is developed. This is done using a version of the sinusoidal analysis-synthesis system that models and independently modifies the phase contributions of the vocal tract and vocal cord excitation. An important property of the system is its ability to perform time-varying rates of change. Extensions of the method are applied to fixed and time-varying pitch modification of speech. The sine-wave analysis-synthesis system also allows for shape-invariant joint time-scale and pitch modification, and allows for the adjustment of the time scale and pitch according to speech characteristics such as the degree of voicing View full abstract»

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  • Estimation of fractal signals from noisy measurements using wavelets

    Publication Year: 1992 , Page(s): 611 - 623
    Cited by:  Papers (114)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB)  

    The role of the wavelet transformation as a whitening filter for 1/f processes is exploited to address problems of parameter and signal estimations for 1/f processes embedded in white background noise. Robust, computationally efficient, and consistent iterative parameter estimation algorithms are derived based on the method of maximum likelihood, and Cramer-Rao bounds are obtained. Included among these algorithms are optimal fractal dimension estimators for noisy data. Algorithms for obtaining Bayesian minimum-mean-square signal estimates are also derived together with an explicit formula for the resulting error. These smoothing algorithms find application in signal enhancement and restoration. The parameter estimation algorithms find application in signal enhancement and restoration. The parameter estimation algorithms, in addition to solving the spectrum estimation problem and to providing parameters for the smoothing process, are useful in problems of signal detection and classification. Results from simulations are presented to demonstrated the viability of the algorithms View full abstract»

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  • The reconstruction of a band-limited function and its Fourier transform from a finite number of samples at arbitrary locations by singular value decomposition

    Publication Year: 1992 , Page(s): 559 - 570
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (952 KB)  

    A method for the stable interpolation of a bandlimited function known at sample instants with arbitrary locations in the presence of noise is given. Singular value decomposition is used to provide a series expansion that, in contrast to the method of sampling functions, permits simple identification of vectors in the minimum-norm space poorly represented in the sample values. Three methods, Miller regularization, least squares estimation, and maximum a posteriori estimation, are given for obtaining regularized reconstructions when noise is present. The singular value decomposition (SVD) method is used to interrelate these methods. Examples illustrating the technique are given View full abstract»

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  • Automatic determination of reject thresholds in classifiers employing discriminant functions

    Publication Year: 1992 , Page(s): 711 - 713
    Cited by:  Papers (2)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB)  

    In most statistical pattern classifiers, each class has different error probabilities. If a reject threshold is introduced, the error and reject probabilities can still vary widely for different classes. An algorithm is developed for finding separate reject thresholds for each class in order to attempt to equalize the probabilities. A gradient approach is used to minimize a measure of the difference between the desired and actual reject and error probabilities for each class. Examples are given for a Gaussian classifier of handprinted numerals. However, the method is applicable in any classifier employing discriminant functions. It is possible to significantly improve the tradeoff between error and reject probabilities, when the thresholds are allowed to be different for each class View full abstract»

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  • Variable bit rate adaptive predictive coder

    Publication Year: 1992 , Page(s): 511 - 517
    Cited by:  Papers (1)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (620 KB)  

    An adaptive predictive coder providing almost toll quality at 16 kb/s and minimal degradation when the bit rate is lowered to 9.6 kb/s is described. The coder can operate at intermediate bit rates and can also change bit rate on a packet-by-packet basis. Variable bit rate operation is achieved through the use of switched quantization, thus eliminating the need for buffering of the output. A noise shaping filter provides flexible control of the output noise spectrum. The filter, in conjunction with an enhanced way to adapt the quantizer step size, which tries to accommodate the quantization noise feedback, accounts for the toll quality. By quantizing the residue with more than one quantizer, the effective number of bits per sample can be controlled in a deterministic way regardless of the entropy residue. The lower limit of operation is at 9.6 kb/s. Performance of the coder under random bit errors is also presented. It has been found that only at error rates of 10-2 and higher does the degradation becomes objectionable View full abstract»

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  • Noniterative subspace tracking

    Publication Year: 1992 , Page(s): 571 - 577
    Cited by:  Papers (72)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (500 KB)  

    A rank-one spherical subspace update that is appropriate for subspace-based methods like MUSIC and minimum norm is introduced. This noniterative, highly parallel, numerically stabilized, subspace update is closely related to rank-one eigenstructure updating. However, a rank-one subspace update involves less computation than simple rank-one correlation accumulation. Moreover. The frequency tracking capabilities of the noniterative subspace update are virtually identical to and in some case more robust than the more computationally expensive eigen-based methods View full abstract»

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  • Adaptive entropy-coded predictive vector quantization of images

    Publication Year: 1992 , Page(s): 633 - 644
    Cited by:  Papers (22)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1284 KB)  

    The authors consider 2-D predictive vector quantization (PVQ) of images subject to an entropy constraint and demonstrate the substantial performance improvements over existing unconstrained approaches. They describe a simple adaptive buffer-instrumented implementation of this 2-D entropy-coded PVQ scheme which can accommodate the associated variable-length entropy coding while completely eliminating buffer overflow/underflow problems at the expense of only a slight degradation in performance. This scheme, called 2-D PVQ/AECQ (adaptive entropy-coded quantization), is shown to result in excellent rate-distortion performance and impressive quality reconstructions of real-world images. Indeed, the real-world coding results shown demonstrate little distortion at rates as low as 0.5 b/pixel View full abstract»

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  • Analysis of the spatial filtering approach to the decorrelation of coherent sources

    Publication Year: 1992 , Page(s): 692 - 694
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB)  

    The recently proposed spatial filtering, which is developed to effectively decorrelate coherent signals, is analyzed. It has been shown that any set of distinct preliminary estimates of directions of arrival (DOAs) can be used to obtain a full rank source covariance matrix. In addition, a particular signal enhancement approach is developed to minimize the effects of the sensor noise. Statistical analysis of the spatial filtering and its enhanced version are also studied using the Monte Carlo method View full abstract»

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  • Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding

    Publication Year: 1992 , Page(s): 518 - 531
    Cited by:  Papers (32)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1256 KB)  

    Fast search algorithms are proposed and studied for vector quantization encoding using the K-dimensional (K-d) tree structure. Here, the emphasis is on the optimal design of the K -d tree for efficient nearest neighbor search in multidimensional space under a bucket-Voronoi intersection search framework. Efficient optimization criteria and procedures are proposed for designing the K-d tree, for the case when the test data distribution is available (as in vector quantization application in the form of training data) as well as for the case when the test data distribution is not available and only the Voronoi intersection information is to be used. The criteria and bucket-Voronoi intersection search procedure are studied in the context of vector quantization encoding of speech waveform. They are empirically observed to achieve constant search complexity for O(log N) tree depths and are found to be more efficient in reducing the search complexity. A geometric interpretation is given for the maximum product criterion, explaining reasons for its inefficiency with respect to the optimization criteria View full abstract»

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  • Relationships among digital one/half band filters, low/high order differentiators, and discrete/differentiating Hilbert transformers

    Publication Year: 1992 , Page(s): 694 - 700
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (376 KB)  

    There exists a close relationship among digital one-/half-band filters, low-/high-order differentiators, and discrete/differentiating Hilbert transformers. A complete picture of their interrelationships and conversions between each other is presented. A useful table and some block diagrams have been developed for their impulse responses' connections, and a design example is given for illustration View full abstract»

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  • Minimum-variance deconvolution and maximum-likelihood deconvolution for nonwhite Bernoulli-Gaussian processes with a Joseph spectrum

    Publication Year: 1992 , Page(s): 676 - 679
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB)  

    Todoeschuck and Jensen (1988) recently reported that the reflectivity sequences, denoted p(k), calculated from some sonic logs are not white and have a power spectral density approximately proportional to frequency, called a Joseph spectrum. It is shown here how to compute the minimum-variance estimate and maximum-likelihood estimate for a μ(k) modeled as a nonwhite Bernoulli-Gaussian (B-G) process with a Joseph spectrum. Also presented are the corresponding estimates for a statistically equivalent white B-G process μ*(k) which mimics μ(k). Some conclusions regarding the acceptability of these estimates are drawn View full abstract»

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  • On the quality of recursively identified FIR models

    Publication Year: 1992 , Page(s): 679 - 682
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB)  

    The author considers recursive identification of time-varying systems having finite impulse response, focusing on the tradeoff between tracking capability and disturbance rejection. Approximate, but simple and explicit, frequency-domain expressions for the model quality are derived for three different identification algorithms. The results, derived under the assumption of slow adaptation, slow system variation, and high model order, are extensions of the results presented by Gunnarsson and Ljung (see ibid., vol.37, p.1072, 1989) to the case where the system output is affected by correlated disturbances View full abstract»

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  • One-dimensional Hadamard naturalness-preserving transform reconstruction of signals degraded by nonstationary noise processes

    Publication Year: 1992 , Page(s): 645 - 659
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1316 KB)  

    The problem of reconstructing a time-varying one-dimensional signal from segments of its Hadamard naturalness preserving transform (NPT) is considered. Closed-form reconstruction formulas are derived for specific formats of available Hadamard NPT segments. Two fast reconstruction schemes, which in a single iteration provide the same solution as the general iterative reconstruction algorithm, are introduced for these formats. Simulation results of the algorithms when applied to first-order Gauss-Markov and image signals are good. However, the reconstruction of speech signals is poor due to the poor estimates derived from the available segments of the transformed signal. The reconstruction algorithm is proposed for interframe two-layer packet transmission of image signals over an Orwell-ring-based network. Good pictorial results are obtained at up to 50% packet loss rate View full abstract»

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  • Initialization for improved IIR filter performance

    Publication Year: 1992 , Page(s): 543 - 550
    Cited by:  Papers (24)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (592 KB)  

    A new method for initializing the memory registers of infinite impulse response (IIR) filters is introduced. In addition to providing improved performance as compared to other methods of initialization, this method is unique in that it makes no prior assumptions regarding the input-signal content. Therefore, the method applies equally well to a variety of IIR filter designs and applications. The method is best suited for signal processing applications in which `batch' processing of the data is used. However, sequential processing, can be accommodated when delays at the beginning of a processing segment can be tolerated View full abstract»

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  • Signal reconstruction from the phase of the bispectrum

    Publication Year: 1992 , Page(s): 601 - 610
    Cited by:  Papers (26)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (840 KB)  

    The authors present a simple procedure, the bispectrum signal reconstruction (BSR) algorithm, to recover the Fourier phase of a signal from the phase of its bispectrum. By simple analogy, a procedure that recovers the Fourier magnitude of a signal from the magnitude of its bispectrum is also presented. In addition, the authors propose an iterative scheme, the bicepstrum iterative reconstruction algorithm (BIRA), for the reconstruction of a finite impulse response (FIR) sequence from only the phase of its bispectrum, and they demonstrate how some a priori information on the energy of the cepstra coefficients can improve significantly the convergence rate of the algorithm. Both schemes are based on the key observation that the differences of the bispectrum coefficients contain all the information concerning the Fourier phase of the signal, whereas their sums contain the Fourier-magnitude information View full abstract»

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  • Modeling of ultrasound speckle with application in flaw detection in metals

    Publication Year: 1992 , Page(s): 624 - 632
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1060 KB)  

    RF ultrasound backscatter speckle is modeled by a parametric noncausal Gaussian Markov field that appears to capture the speckle structure well, is consistent with the first-order marginal statistics of the complex amplitude speckle, and explains the homogeneous coarseness appearance of the speckle in terms of a homogeneous colored random field with a definite correlation structure. The Markov property results in the compact parametrization of the backscatter echo field by a few parameters, and constitutes a huge reduction in the representation and analysis complexity of the backscatter image. Use is made of the intensity as well as phase information, associated with the acoustic image by analyzing and modeling the acoustic RF data rather than the intensity data. The additional phase information associated with the RF data allows for the statistics of the complex backscatter echo field or, equivalently, that of the RF field to be completely specified. The approach provides a coherent theoretical basis for the design of statistical tests for detecting targets embedded in the speckle image, for the case where the speckle model parameters are either a priori known or unknown View full abstract»

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  • A note on `Notch Fourier transform' [by Y. Tadokodo and K. Abe]

    Publication Year: 1992 , Page(s): 690 - 691
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (136 KB)  

    In the above-titled paper (see ibid., vol.ASSP-35, p.1282, Sept. 1987), Tadokodo and Abe presented a clever method to compute the Fourier coefficients at arbitrary frequencies. But their proof of (16) is incomplete, since in their proof the number of sampled data N is assumed to be power of two (i.e., N=2q). However, N=2r, where r is the number of frequency components to be analyzed, is not a necessary power of two even in the discrete Fourier transform (DFT) case. The note gives a complete proof on their (16) without any restrictions on N View full abstract»

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  • Performance degradation of DOA estimators due to unknown noise fields

    Publication Year: 1992 , Page(s): 686 - 690
    Cited by:  Papers (24)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (428 KB)  

    A statistical performance analysis of subspace-based directions-of-arrival (DOA) estimation algorithms in the presence of correlated observation noise with unknown covariance is presented. The analysis of five different estimation algorithms is unified by a single expression for the mean-squared DOA estimation error which is derived using a subspace perturbation expansion. The analysis assumes that only a finite amount of array data is available View full abstract»

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  • Approximation of FIR by IIR digital filters: an algorithm based on balanced model reduction

    Publication Year: 1992 , Page(s): 532 - 542
    Cited by:  Papers (60)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (864 KB)  

    An algorithm for the approximation of finite impulse response (FIR) filters by infinite impulse response (IIR) filters is presented. The algorithm is based on a concept of balanced model reduction. The matrix inversions normally associated with this procedure are notoriously error prone due to ill conditioning of the special matrix forms required. This difficulty is circumvented here by directly formulating a reduced state-space system description which is input/output equivalent to the system that would more conventionally be obtained following the explicit step of constructing an (interim) balanced realization. Examples of FIR by IIR filter approximations are included View full abstract»

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  • Improved tracking adaptive noise canceler for nonstationary environments

    Publication Year: 1992 , Page(s): 700 - 703
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    The performance of multiple reference adaptive noise cancelers is investigated and a new filter structure is proposed that provides better tracking in the multipath, multisource, nonstationary automobile noise environment studied. The filter uses the least mean square (LMS) algorithm with multiple filtering stages and subbanded sections to improve the overall tracking performance while maintaining filter stability View full abstract»

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  • Analysis of subspace fitting and ML techniques for parameter estimation from sensor array data

    Publication Year: 1992 , Page(s): 590 - 600
    Cited by:  Papers (83)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (896 KB)  

    It is shown that the multidimensional signal subspace method, termed weighted subspace fitting (WSF), is asymptotically efficient. This results in a novel, compact matrix expression for the Cramer-Rao bound (CRB) on the estimation error variance. The asymptotic analysis of the maximum likelihood (ML) and WSF methods is extended to deterministic emitter signals. The asymptotic properties of the estimates for this case are shown to be identical to the Gaussian emitter signal case, i.e. independent of the actual signal waveforms. Conclusions concerning the modeling aspect of the sensor array problem are drawn View full abstract»

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  • Glottal source estimation using a sum-of-exponentials model

    Publication Year: 1992 , Page(s): 682 - 686
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    An algorithm for estimating the glottal source waveform in voiced speech is described. The glottal source waveform is described using the LF model proposed by Fant et al. (1985). The vocal tract filter is modeled as a pole-zero system. The analysis of vowel sounds from several talkers shows that the analysis procedure leads to an accurate estimate of the glottal source 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