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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 8 • Date Aug 1990

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Displaying Results 1 - 22 of 22
  • A frequency domain weighting function approach to extrapolation

    Page(s): 1395 - 1402
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    A new extrapolation algorithm has been developed which is linear, noise tolerant, and computationally efficient. A bandwidth measure is defined in terms of a general frequency weighting function, and the extrapolated signal is calculated as the signal that minimizes this measure. The minimization involves the solution of a Toeplitz set of linear equations. Several properties of this technique are developed that are useful in gaining insight into the form of a solution. The algorithm is more efficient than any of its predecessors, since the coefficients of the equations have closed forms. A second advantage of the algorithm is that it is not restricted to band-limited signals. A third advantage of this technique is that it is linear View full abstract»

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  • An improved Burg-type recursive lattice method for autoregressive spectral analysis

    Page(s): 1437 - 1445
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    A new, efficient recursive lattice method for autoregressive spectral analysis is presented. This method is based on an estimate of the covariance matrix, which is Toeplitz, while allowing an unbiased estimation of the frequencies of sinusoidal signals. The algorithm works recursively similarly to Burg's (1975) algorithm for maximum entropy autoregressive spectral estimation. It is shown that for truncated sinusoids in additive white noise, this method is superior to the original Burg's algorithm in resolution, positional bias (it is unbiased in the absence of noise), and spurious peaks in the spectrum, while having about the same arithmetic complexity. It also has better finite precision properties than the Levinson algorithm View full abstract»

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  • Analysis/synthesis techniques for subband image coding

    Page(s): 1446 - 1456
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    Analysis/synthesis systems designed for low bit rate image coding, their impact on overall system quality, and their computational complexity are discussed. The investigation focuses on the design of analysis/synthesis systems for image coding and the perceptual impact of these systems at low bit rates. Two objectives are emphasized in developing these systems: confining the total size of the subband images to be equal to the original image size, and designing the filters so that perceptual distortion is not introduced by the analysis/synthesis system. Methods based on circular convolution and symmetric extensions are developed and discussed in detail. The theory, design, and implementation of both recursive and nonrecursive filtering systems are discussed. Methods are introduced which display advantages over conventional quadrature mirror filter based approaches View full abstract»

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  • A new bit reversal algorithm

    Page(s): 1472 - 1473
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    A new bit reversal permutation algorithm is described. Such algorithms are needed for radix 2 (or radix B) fast Fourier transforms (FFTs) or fast Hartley transforms (FHTs). This algorithm is an alternative to one described by Evans (1987). A BASIC version of this algorithm ran slightly faster than the BASIC version of Evans' algorithm given by Bracewell (1986), with some time savings for odd powers of two. This new algorithm also allows for precomputation of seed tables up to one higher power of two than Evans' algorithm View full abstract»

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  • Estimation of structured covariance matrices and multiple window spectrum analysis

    Page(s): 1467 - 1472
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    A close relationship between low rank modeling and multiple window spectrum estimation is demonstrated by using maximum likelihood estimates of structured covariance matrices. The power in a narrow spectral band is estimated by estimating the variances in a low rank signal plus noise covariance model. This model is swept through the entire frequency band to obtain an estimate of power as a function of frequency. The resulting spectrum estimates are given by weighted combinations of eigenspectra. Each eigenspectrum results from projecting the data onto an orthogonal component of the signal subspace and squaring. The multiple window spectrum estimates of Thomson (1982) correspond to a particular choice for the low rank signal model. The low rank modeling and structured covariance matrix framework is also used to derive the maximum likelihood estimate for the center frequency of a signal in noise. This estimate is also obtained from a weighted combination of eigenspectra View full abstract»

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  • Limit cycles due to roundoff in state-space digital filters

    Page(s): 1460 - 1462
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    A deterministic analysis is presented for limit cycles due to roundoff in state-space digital filters. Two new sufficient conditions are established for the roundoff stability, i.e. suppression of limit cycles, in digital filters. Using these results, restrictions on the location of poles are found for various realizations to be free from roundoff limit cycles View full abstract»

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  • An RNS discrete Fourier transform implementation

    Page(s): 1386 - 1394
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    A novel discrete Fourier transform (DFT) implementation is described. It is based on the union of number theoretic transforms, modular arithmetic, and distributed arithmetic. In order to achieve megahertz-class transform rates with a limited amount of hardware, several new technologies are integrated. To accelerate complex arithmetic speed, a new body of knowledge called the quadratic residue number system (QRNS) is employed. To overcome the overflow management problem introduced by the QRNS, a finite impulse response form of the DFT, known as the prime factor transform (PFT), is used. In order to implement the PFT and the required QRNS overflow scaling units, a fast and compact distributed arithmetic filter (DAF) and number system converter is designed. The integrated system is developed and analyzed in the context of existing semiconductor technology. The resulting machine is shown to potentially possess megahertz-class performance, over a 16- to 24-bit data dynamic range, in a limited amount of hardware View full abstract»

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  • Cumulant-based order determination of non-Gaussian ARMA models

    Page(s): 1411 - 1423
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    The objective is the order determination of non-Gaussian and nonminimum phase autoregressive moving average (ARMA) models, using higher-order cumulant statistics. The two methods developed assume knowledge of upper bounds on the ARMA orders. The first method performs a linear dependence search among the columns of a higher-order statistics matrix by means of the Gram-Schmidt orthogonalization procedure. In the second method, the order of the AR part is found as the rank of the matrix formed by the higher-order statistics sequence. For numerically robust rank determination the singular value decomposition approach is adopted. The argument principle and samples of the polyspectral phase are used to obtain the relative degree of the ARMA model, from which the order of the MA part can be determined. Statistical analysis is included for determining the correct MA order with high probability, when estimates of third-order cumulants are only available. Simulations are used to verify the performance of the methods and compare autocorrelation with cumulant-based order determination approaches View full abstract»

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  • Adaptive iterative algorithms for spiky deconvolution

    Page(s): 1462 - 1466
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    Considering the joint detection-estimation character that spiky deconvolution problems have, an adaptively contracted (projection) selection operator is introduced to detect the nonzero values of the solution, which can be combined with iterative algorithms to offer very efficient schemes for solving these problems. A number of gradient-type algorithms based on this principle are described, and their performance is illustrated through simulation examples. The approach is based on the idea of reducing the noise and defining the signal in an iterative form. Another possibility is to define the signal and reduce the overall energy outside its domain, also in an iterative form. This algorithm is more expensive from a computational point of view; however, simulations indicate that it has somewhat different properties. It seems to be slightly less robust against the noise, while it offers better resolution and even more accurate amplitude estimates View full abstract»

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  • Code design and performance characterization for code multiplexed imaging

    Page(s): 1321 - 1329
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (788 KB)  

    A new sonar imaging technique which uses coded waveforms to project different sound signals in different directions has bee proposed. In this context, the problem of creating a set of frequency-hopped code words that have mutually small correlation properties has arisen. The design and performance characterization of frequency-hopped signals for multibeam sonar imaging are discussed. The two special cases considered are the fully coherent case, and the incoherent case when medium perturbations destroy the phase coherence. Two systematic design techniques are presented that are based on elements of the Galois field GF(p), where p is a prime number. One technique uses first-order Reed-Solomon code words in order to generate p code words of length p-1. The other technique is an empirical design technique which generates p-1 code words of length p View full abstract»

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  • Parameter estimation of exponentially damped sinusoids using higher order statistics

    Page(s): 1424 - 1436
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    A new approach for the estimation of the parameters of exponentially damped sinusoids is introduced based on third- or fourth-order statistics of the observation signal. The method may be seen as an extension of the minimum norm principal eigenvectors method to higher order statistics domains. The strong points and limitations of the method are discussed as well as sufficient conditions for the existence of the solution. The utilization of the method in the case of finite length signals in the presence of additive Gaussian noise (white or colored) is addressed. Monte Carlo simulations demonstrate the effectiveness of the new method when the additive noise is colored Gaussian with unknown autocorrelation sequence for different signal-to-noise ratios and a single data record. The case of an ensemble of data records is studied when the exponentially damped sinusoids are assumed to have random phase View full abstract»

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  • Finite precision arithmetic and the Schur algorithm

    Page(s): 1475 - 1478
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    The numerical behavior of the Schur algorithm under fixed-point arithmetic conditions is investigated. It was found that the variance of the reflection coefficient estimates is large when the autocorrelation coefficients used to obtain the estimates are obtained from a narrowband low-pass signal. This is because such signals yield ill-conditioned autocorrelation matrices and is not due to numerical instability in the Schur algorithm. The effects of quantization errors tend to propagate through the later stages of the reflection coefficient computation in this instance. As a result, the Schur algorithm has numerical properties similar to those of the Durbin algorithm View full abstract»

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  • Recursive maximum likelihood estimation of complex autoregressive processes

    Page(s): 1466 - 1467
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    The recursive maximum likelihood estimation (RMLE) algorithm conceived by Kay (see ibid., vol.ASSP-31, p.56, 1983) is extended to complex data sets. The complex version requires the same level of computation as that for real data. The original development was restricted to the case of realm data. The purpose is to extend RMLE to the more universal realm of complex data. The derivation is discussed. It is argued, without direct proof, that the algorithm is stable in the sense that the magnitude of the reflection coefficient at each step is less than unity View full abstract»

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  • Reduced-rank least squares channel estimation

    Page(s): 1403 - 1410
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    A reduced-rank least squares (RRLS) algorithm based on oversampling the channel output by an integer factor and singular value decomposition (SVD) of a data matrix is shown to have certain advantages over the nonparametric least-squares (LS) and the parametric Evans and Fischl (EF) alternative algorithm for estimating the pulse response of a truncated equivalent baseband communication channel. By sampling the channel output faster than the training symbol rate and applying SVD to the data matrix formed from the observed data, the method is shown to exhibit improved-error performance over existing nonparametric LS methods and the parametric EF iterative algorithm. The RRLS algorithm's performance has been shown to be somewhat sensitive to model order selection and observation noise statistics. The normalized mean squared error (MSE) performance of the RRLS algorithm is shown to be essentially independent of oversampling factors that are not much greater than the span of the truncated channel. It performs well even in severe noise environments View full abstract»

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  • A comparison between two measures of convergence in recursive-window based spectrum estimation

    Page(s): 1457 - 1459
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    It is shown that approximations of the infinite impulse response (IIR) of a single-pole filter by a rectangular finite impulse response (FIR) through either the effective window length approach or the least squares inverse filtering approach yield the same results. Both the least squares inverse filter method and the effective window length can be used as measures of convergence in recursive-window based spectrum estimators. An algebraic proof is given to show that both measures take the same value for the commonly used single-pole exponential window View full abstract»

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  • HF channel estimation using a fast transversal filter algorithm

    Page(s): 1353 - 1362
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    The estimation of the sampled impulse response of a time-varying HF channel using a fast transversal filter (FTF) algorithm is studied. The latter is a computationally efficient implementation of the recursive least squares (RLS) algorithm, developed from the conventional Kalman filter. The application is that of digital data transmission. A novel stabilization technique is proposed to overcome the problem caused by the accumulation of roundoff errors, and, in addition, degree-one prediction is incorporated into the algorithm to improve the effectiveness of the estimation process. Various estimators are described, the results of a series of computer-simulation tests are presented, and the accuracies of the channel estimates given by the different systems are compared. The new FTF algorithm gives a substantially better performance than the conventional algorithm from which it is derived, and it involves only a small increase in complexity View full abstract»

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  • The performance of time-dependent adaptive filters for interference rejection

    Page(s): 1373 - 1385
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    Time-dependent adaptive filters (TDAFs) that allow for the cyclostationary nature of communication signals by periodically changing the filter and adaptation parameters are examined. The TDAF has an advantage over the conventional time-independent adaptive filter in achieving better performance, i.e. reduced mean square error (MSE), for signals with periodic statistics. The basic theory of the TDAF is presented. The TDAF is shown to be more effective than the time-independent adaptive filter for interference rejection. This is verified by theoretical analysis and computer simulation of specific cases of extracting a signal in noise or interference. The criteria for judging the performance of the TDAF for interference rejection are MSE, bit error rate measurements, and constellation diagrams View full abstract»

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  • Nonconvexity of the stability domain of digital filters

    Page(s): 1459 - 1460
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    The stability of a causal digital filter with a rational transfer function H(z) is completely specified by the location of its poles with respect to the unit circle (UC). The set of points A corresponding to stable filters, i.e. to polynomials P with roots inside the UC, is called the stability domain Σ of digital filters. Results are established that concern the convexity of Σ. The denominator of a rational digital filter of nth order is a polynomial represented by a point A of the n-dimensional space of its coefficients. It is shown that for n⩾3, Σ is not convex and especially if point A belongs to Σ and a satisfies 0<a⩽1, then point aA does not necessarily belong to Σ View full abstract»

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  • On the max/median filter

    Page(s): 1473 - 1475
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    A max/min median filter, as an extension of the max/median filter, is presented. Theoretical analysis shows that the max/min median filter can give a smaller bias than the max/median filter. An example shows that the performance of the max/min median filter is better than that of the max/median filter in preserving the details of images View full abstract»

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  • Frequency analysis and synthesis of a class of nonlinear filters

    Page(s): 1363 - 1372
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    Nonlinear filters are analyzed from a spectral point of view. The equivalent frequency behavior of a filter is described by its linear part, which represents the linear nonrecursive filter, that best matches, in the mean-square sense, the behavior of the filter. The class considered includes all the order statistic filters (L-filters) such as median, midrange, alpha-trim, and some new order statistic filters (Ll-filters) defined by the authors to generalize L-filters and FIR filters. The formulation leads to a technique for imposing on the nonlinear filters a given spectral behavior. A simulation of the design for a low-pass Ll-filter is given View full abstract»

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  • Fast methods for the CELP speech coding algorithm

    Page(s): 1330 - 1342
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    Special fast procedures for the code excited linear predictive coding (CELP) algorithm have been developed to make implementation on modest hardware possible. The advantages, as well as the disadvantages, of the various fast procedures are discussed. A general formalism for the algorithm is developed, followed by the discussion of the individual procedures which are grouped according to their features. Along with the computational complexity of each procedure, its storage requirement and numerical accuracy are discussed. A large number of the fast procedures are designed to search through a particular type of codebook (most of the codebooks are stochastic in character, while a few are deterministic). Other fast procedures can be used for arbitrary codebooks and are thus also applicable to trained codebooks. Some of the fast procedures designed for stochastic codebooks can also be used for the computation of the closed pitch loop parameters, which can be interpreted as a search through a time-dependent codebook View full abstract»

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  • A fast adaptive filter algorithm using eigenvalue reciprocals as stepsizes

    Page(s): 1343 - 1352
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    It is shown that there exist finite optimum update positions in the gradient direction of the least-mean-square (LMS) algorithm. The optimum stepsizes to reach these positions are in a discrete set. On this basis, a new adaptive filter (ADF) algorithm is proposed. The discrete cosine transform, a fairly good approximation of the Karhunen-Loeve transform for a large number of signal classes, is used to estimate the optimum stepsizes. A block-averaging operation is also used for smoothing the gradient estimate. Computer simulations show that the proposed ADF algorithm provides fast convergence rates when the input signal autocorrelation matrix has either large or small eigenvalue spread (ratio of the largest to the smallest eigenvalues). The number of multiplications required by the new ADF is about 11 log2 (N)+12, which is comparable to the 10 log2 (N )+8 required by the fast LMS algorithm 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