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Showing papers on "Adaptive filter published in 1996"


Book
01 Jan 1996

3,808 citations


Book
19 Apr 1996
TL;DR: The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering.
Abstract: From the Publisher: The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. Also features an abundance of interesting and challenging problems at the end of every chapter.

2,549 citations


Journal ArticleDOI
TL;DR: A class of adaptive algorithms for source separation that implements an adaptive version of equivariant estimation and is henceforth called EASI, which yields algorithms with a simple structure for both real and complex mixtures.
Abstract: Source separation consists of recovering a set of independent signals when only mixtures with unknown coefficients are observed. This paper introduces a class of adaptive algorithms for source separation that implements an adaptive version of equivariant estimation and is henceforth called equivariant adaptive separation via independence (EASI). The EASI algorithms are based on the idea of serial updating. This specific form of matrix updates systematically yields algorithms with a simple structure for both real and complex mixtures. Most importantly, the performance of an EASI algorithm does not depend on the mixing matrix. In particular, convergence rates, stability conditions, and interference rejection levels depend only on the (normalized) distributions of the source signals. Closed-form expressions of these quantities are given via an asymptotic performance analysis. The theme of equivariance is stressed throughout the paper. The source separation problem has an underlying multiplicative structure. The parameter space forms a (matrix) multiplicative group. We explore the (favorable) consequences of this fact on implementation, performance, and optimization of EASI algorithms.

1,417 citations


Journal ArticleDOI
TL;DR: A guide to using artificial intelligence in the filmmaking process, as well as practical suggestions for improving the quality and efficiency of existing and new approaches.

1,226 citations


Journal ArticleDOI
TL;DR: The genetic algorithm is introduced as an emerging optimization algorithm for signal processing and a number of applications, such as IIR adaptive filtering, time delay estimation, active noise control, and speech processing, that are being successfully implemented are described.
Abstract: This article introduces the genetic algorithm (GA) as an emerging optimization algorithm for signal processing. After a discussion of traditional optimization techniques, it reviews the fundamental operations of a simple GA and discusses procedures to improve its functionality. The properties of the GA that relate to signal processing are summarized, and a number of applications, such as IIR adaptive filtering, time delay estimation, active noise control, and speech processing, that are being successfully implemented are described.

1,093 citations


Journal ArticleDOI
TL;DR: Weighted median (WM) filters have the robustness and edge preserving capability of the classical median filter and resemble linear FIR filters in certain properties as discussed by the authors, which enables the use of the tools developed for the latter class in characterizing and analyzing the behavior and properties of WM filters.
Abstract: Weighted Median (WM) filters have the robustness and edge preserving capability of the classical median filter and resemble linear FIR filters in certain properties. Furthermore, WM filters belong to the broad class of nonlinear filters called stack filters. This enables the use of the tools developed for the latter class in characterizing and analyzing the behavior and properties of WM filters, e.g. noise attenuation capability. The fact that WM filters are threshold functions allows the use of neural network training methods to obtain adaptive WM filters. In this tutorial paper we trace the development of the theory of WM filtering from its beginnings in the median filter to the recently developed theory of optimal weighted median filtering. Applications discussed include: idempotent weighted median filters for speech processing, adaptive weighted median and optimal weighted median filters for image and image sequence restoration, weighted medians as robust predictors in DPCM coding and Quincunx coding, and weighted median filters in scan rate conversion in normal TV and HDTV systems.

626 citations


01 Jan 1996

355 citations


Journal ArticleDOI
TL;DR: A new efficient algorithm for Gabor-filter design is presented, along with methods for estimating filter output statistics, which typically requires an order of magnitude less computation to design a filter than a previously proposed method.

339 citations


Journal ArticleDOI
D. Frey1
TL;DR: In this paper, a new method of analog filter design is proposed where nonlinear active components are a natural part of a filter realizing an overall linear transfer function, which is articulated in the generation of the class of so-called "Exponential State Space" (ESS) filters.
Abstract: A new method of analog filter design is proposed where nonlinear active components are a natural part of a filter realizing an overall linear transfer function. This approach to design is articulated in the generation of the class of so-called "Exponential State Space" (ESS) filters. An outgrowth of "log filters", ESS filters are created via a mapping on the state space of a linear filter. Specifically, the state variables are equal to simple functions of exponentials or node voltages. The use of exponential, hyperbolic tangent, and hyperbolic sine mappings is shown to produce realizable nodal equations that result in "log", "tanh" and "sinh" filters, respectively. Aspects of interpretation and realization of the transformed state equations are discussed. It is shown that sinh filters are class AB filters, which is an intriguing extension of a concept introduced by Seevinck (1990). The different filter types are compared to an analogous standard transconductance-C filter via simulation of a band-pass filter with a Q of 5. All filters demonstrate tunability over a 100 to 1 range with excellent frequency response stability and accuracy over the tuning range, which extends to 5 MHz. These results and IMD and noise performance are given using both ideal transistors and transistors whose cutoff frequency equals approximately 300 MHz.

266 citations


Journal ArticleDOI
TL;DR: It is shown that the celebrated least-mean squares (LMS) adaptive algorithm is H/sup /spl infin// optimal, and it is established that it is a minimax filter, which minimizes the maximum energy gain from the disturbances to the predicted errors.
Abstract: We show that the celebrated least-mean squares (LMS) adaptive algorithm is H/sup /spl infin// optimal. The LMS algorithm has been long regarded as an approximate solution to either a stochastic or a deterministic least-squares problem, and it essentially amounts to updating the weight vector estimates along the direction of the instantaneous gradient of a quadratic cost function. We show that the LMS can be regarded as the exact solution to a minimization problem in its own right. Namely, we establish that it is a minimax filter: it minimizes the maximum energy gain from the disturbances to the predicted errors, whereas the closely related so-called normalized LMS algorithm minimizes the maximum energy gain from the disturbances to the filtered errors. Moreover, since these algorithms are central H/sup /spl infin// filters, they minimize a certain exponential cost function and are thus also risk-sensitive optimal. We discuss the various implications of these results and show how they provide theoretical justification for the widely observed excellent robustness properties of the LMS filter.

239 citations


Book ChapterDOI
15 Apr 1996
TL;DR: It is shown that most classical techniques used to design finite impulse response (FIR) digital filters can also be used toDesign significantly faster surface smoothing filters and an algorithm to estimate the power spectrum of a signal is described.
Abstract: Smooth surfaces are approximated by polyhedral surfaces for a number of computational purposes. An inherent problem of these approximation algorithms is that the resulting polyhedral surfaces appear faceted. Within a recently introduced signal processing approach to solving this problem [7, 8], surface smoothing corresponds to low-pass filtering. In this paper we look at the filter design problem in more detail. We analyze the stability properties of the low-pass filter described in [7, 8], and show how to minimize its running time. We show that most classical techniques used to design finite impulse response (FIR) digital filters can also be used to design significantly faster surface smoothing filters. Finally, we describe an algorithm to estimate the power spectrum of a signal, and use it to evaluate the performance of the different filter design techniques described in the paper.

Journal ArticleDOI
TL;DR: The DWCE algorithm is introduced and results of a preliminary study based on 25 digitized mammograms with biopsy proven masses are presented, which compares morphological feature classification based on sequential thresholding, linear discriminant analysis, and neural network classifiers for reduction of false-positive detections.
Abstract: Presents a novel approach for segmentation of suspicious mass regions in digitized mammograms using a new adaptive density-weighted contrast enhancement (DWCE) filter in conjunction with Laplacian-Gaussian (LG) edge detection. The DWCE enhances structures within the digitized mammogram so that a simple edge detection algorithm can be used to define the boundaries of the objects. Once the object boundaries are known, morphological features are extracted and used by a classification algorithm to differentiate regions within the image. This paper introduces the DWCE algorithm and presents results of a preliminary study based on 25 digitized mammograms with biopsy proven masses. It also compares morphological feature classification based on sequential thresholding, linear discriminant analysis, and neural network classifiers for reduction of false-positive detections.

Journal ArticleDOI
TL;DR: Discusses the application of neural networks to general and radial basis functions and in particular to adaptive equalization and interference rejection problems, and neural-network-based algorithms show promise in spread spectrum systems.
Abstract: Discusses the application of neural networks to general and radial basis functions and in particular to adaptive equalization and interference rejection problems. Neural-network-based algorithms strike a good balance between performance and complexity in adaptive equalization, and show promise in spread spectrum systems.

Journal ArticleDOI
TL;DR: A class of adaptive filters based on sequential adaptive eigendecomposition (subspace tracking) of the data covariance matrix that can be computationally less (or even much less) demanding, depending on the order/rank ratio N/r or the compressibility of the signal.
Abstract: We introduce a class of adaptive filters based on sequential adaptive eigendecomposition (subspace tracking) of the data covariance matrix. These new algorithms are completely rank revealing, and hence, they can perfectly handle the following two relevant data cases where conventional recursive least squares (RLS) methods fail to provide satisfactory results: (1) highly oversampled "smooth" data with rank deficient of almost rank deficient covariance matrix and (2) noise-corrupted data where a signal must be separated effectively from superimposed noise. This paper contradicts the widely held belief that rank revealing algorithms must be computationally more demanding than conventional recursive least squares. A spatial RLS adaptive filter has a complexity of O(N/sup 2/) operations per time step, where N is the filter order. The corresponding low-rank adaptive filter requires only O(Nr) operations per time step, where r/spl les/N denotes the rank of the data covariance matrix. Thus, low-rank adaptive filters can be computationally less (or even much less) demanding, depending on the order/rank ratio N/r or the compressibility of the signal. Simulation results substantiate our claims. This paper is devoted to the theory and application of fast orthogonal iteration and bi-iteration subspace tracking algorithms.

Journal ArticleDOI
TL;DR: A reliable and efficient computational algorithm for restoring blurred and noisy images that can be used in an adaptive/interactive manner in situations when knowledge of the noise variance is either unavailable or unreliable is proposed.
Abstract: A reliable and efficient computational algorithm for restoring blurred and noisy images is proposed. The restoration process is based on the minimal total variation principle introduced by Rudin et al. For discrete images, the proposed algorithm minimizes a piecewise linear l/sub 1/ function (a measure of total variation) subject to a single 2-norm inequality constraint (a measure of data fit). The algorithm starts by finding a feasible point for the inequality constraint using a (partial) conjugate gradient method. This corresponds to a deblurring process. Noise and other artifacts are removed by a subsequent total variation minimization process. The use of the linear l/sub 1/ objective function for the total variation measurement leads to a simpler computational algorithm. Both the steepest descent and an affine scaling Newton method are considered to solve this constrained piecewise linear l/sub 1/ minimization problem. The resulting algorithm, when viewed as an image restoration and enhancement process, has the feature that it can be used in an adaptive/interactive manner in situations when knowledge of the noise variance is either unavailable or unreliable. Numerical examples are presented to demonstrate the effectiveness of the proposed iterative image restoration and enhancement process.

Journal ArticleDOI
V. Dutt1, J.F. Greenleaf
TL;DR: Statistics of log-compressed echo images are used to derive a parameter that can be used to quantify the extent of speckle formation, and can be use with an unsharp masking filter to adaptively reduce Speckle.
Abstract: A good statistical model of speckle formation is useful for designing a good adaptive filter for speckle reduction In ultrasound B-scan images. Previously, statistical models have been used, but they failed to account for the log compression of the echo envelope employed by clinical ultrasound systems. Log-compression helps in reducing the dynamic range of the B-scan Images for display on a monitor as well as enhancing weak backscatters. In this article, statistics of log-compressed echo images, using the K-distribution statistical model for the echo envelope, are used to derive a parameter that can be used to quantify the extent of speckle formation. This speckle quantification can be used with an unsharp masking filter to adaptively reduce speckle. The effectiveness of the filter is demonstrated on images of contrast detail phantoms and on in-vivo abdominal images obtained by a clinical ultrasound system with log-compression.

Journal ArticleDOI
Kaoru Arakawa1
TL;DR: A novel median-type filter controlled by fuzzy rules is proposed in order to remove impulsive noises on signals such as images, and the weight is set based on fuzzy rules concerning the states of the input signal sequence.

Journal ArticleDOI
P.S. Hamilton1
TL;DR: With a 360 Hz sample rate and an adaptation time of approximately 0.3 s for a 1 mV 60-Hz signal, the adaptive implementation is less complex and introduces less noise, particularly in the ST-segment, into a typical ECG signal.
Abstract: We have investigated the relative performance of an adaptive and nonadaptive 60-Hz notch filter applied to an ECG signal. We evaluated the performance of the two implementations with respect to adaptation rate (or transient response time), signal distortion, and implementation complexity. We also investigated the relative effect of adaptive and nonadaptive 60-Hz filtering on ECG data compression. With a 360 Hz sample rate and an adaptation time of approximately 0.3 s for a 1 mV 60-Hz signal, the adaptive implementation is less complex and introduces less noise, particularly in the ST-segment, into a typical ECG signal. When applied to ECG signals, prior to data compression by average beat subtraction and residual differencing, the residual signal resulting from the adaptively filtered signal had an average entropy 0.31 bits per sample (bps) lower than the unfiltered signal. The nonadaptive 60-Hz filter produced an average entropy decrease of 0.08 bps relative to the unfiltered ECG.

Journal ArticleDOI
TL;DR: The algorithm has been designed mainly for 50 Hz to 75 Hz frame rate up-conversion with applications in a multimedia environment, but it can also be used in advanced television receivers to remove artifacts due to low scan rate.
Abstract: A frame interpolation algorithm for frame rate up-conversion of progressive image sequences is proposed. The algorithm is based on simple motion compensation and linear interpolation. A motion vector is searched for each pixel in the interpolated image and the resulting motion field is median filtered to remove inconsistent vectors. Averaging along the motion trajectory is used to produce the interpolated pixel values. The main novelty of the proposed method is the motion compensation algorithm which has been designed with low computational complexity as an important criterion. Subsampled blocks are used in block matching and the vector search range is constrained to the most likely motion vectors. Simulation results show that good visual quality has been obtained with moderate complexity. The algorithm has been designed mainly for 50 Hz to 75 Hz frame rate up-conversion with applications in a multimedia environment, but it can also be used in advanced television receivers to remove artifacts due to low scan rate.

Proceedings ArticleDOI
Osamu Hoshuyama1, A. Sugiyama
07 May 1996
TL;DR: Simulation results show that the proposed beamformer designed to allow about 20 degrees of look-direction error can suppress interference by more than 17 dB and can be implemented with a small number of microphones.
Abstract: This paper proposes a new robust adaptive beamformer applicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a variable blocking matrix using coefficient-constrained adaptive digital filters (CCADFs). The CCADFs minimize leakage of target signal into the interference path of the GSC. Each coefficient of the CCADFs is constrained to avoid mistracking. The input signal to all the CCADFs is the output of a fixed beamformer. In a multiple-input canceller, leaky ADFs are used to decrease undesirable target-signal cancellation. The proposed beamformer can allow large look-direction error with almost no degradation in interference-reduction performance and can be implemented with a small number of microphones. The maximum allowable look-direction error can be specified by the user. Simulation results show that the proposed beamformer designed to allow about 20 degrees of look-direction error can suppress interference by more than 17 dB.

Journal ArticleDOI
TL;DR: This paper presents a structure adaptive anisotropic filtering technique with its application to processing magnetic resonance images that differs from other techniques in that, instead of using local gradients as a means of controlling the anisotropism of filters, it uses both a local intensity orientation and ananisotropic measure of level contours to control the shape and extent of the filter kernel.

Journal ArticleDOI
TL;DR: An algorithmic approach to the design of low-power frequency-selective digital filters based on the concepts of adaptive filtering and approximate processing to reduce the total switched capacitance by dynamically varying the filter order based on signal statistics.
Abstract: We present an algorithmic approach to the design of low-power frequency-selective digital filters based on the concepts of adaptive filtering and approximate processing. The proposed approach uses a feedback mechanism in conjunction with well-known implementation structures for finite impulse response (FIR) and infinite impulse response (IIR) digital filters. Our algorithm is designed to reduce the total switched capacitance by dynamically varying the filter order based on signal statistics. A factor of 10 reduction in power consumption over fixed-order filters is demonstrated for the filtering of speech signals.

Journal ArticleDOI
TL;DR: It is shown that an intrinsic feedback structure can be associated with the varied adaptive schemes and extended the so-called transfer function approach to a general time-variant scenario without any approximations.
Abstract: This paper provides a time-domain feedback analysis of gradient-based adaptive schemes. A key emphasis is on the robustness performance of the adaptive filters in the presence of disturbances and modeling uncertainties (along the lines of H/sup /spl infin//-theory and robust filtering). The analysis is carried out in a purely deterministic framework and assumes no prior statistical information or independence conditions. It is shown that an intrinsic feedback structure can be associated with the varied adaptive schemes. The feedback structure is motivated via energy arguments and is shown to consist of two major blocks: a time-variant lossless (i.e., energy preserving) feedforward path and a time-variant feedback path. The configuration is further shown to lend itself to analysis via a so-called small gain theorem, thus leading to stability and robustness conditions that require the contractivity of certain operators. Choices for the step-size parameter in order to guarantee faster rates of convergence are also derived, and simulation results are included to demonstrate the theoretical findings. In addition, the time-domain analysis provided in this paper is shown to extend the so-called transfer function approach to a general time-variant scenario without any approximations.

Journal ArticleDOI
TL;DR: This paper presents a PR cosine-modulated filter bank where the length of the prototype filter is arbitrary, and the design is formulated as a quadratic-constrained least-squares optimization problem, where the optimized parameters are the prototypefilter coefficients.
Abstract: It is well known that FIR filter banks that satisfy the perfect-reconstruction (PR) property can be obtained by cosine modulation of a linear-phase prototype filter of length N=2mM, where M is the number of channels. In this paper, we present a PR cosine-modulated filter bank where the length of the prototype filter is arbitrary. The design is formulated as a quadratic-constrained least-squares optimization problem, where the optimized parameters are the prototype filter coefficients. Additional regularity conditions are imposed on the filter bank to obtain the cosine-modulated orthonormal bases of compactly supported wavelets. Design examples are given.

Journal ArticleDOI
TL;DR: A new hybrid search methodology is developed in which the genetic-type search is embedded into gradient-descent algorithms (such as the LMS algorithm), which has the characteristics of faster convergence, global search capability, less sensitivity to the choice of parameters, and simple implementation.
Abstract: An "evolutionary" approach called the genetic algorithm (GA) was introduced for multimodal optimization in adaptive IIR filtering. However, the disadvantages of using such an algorithm are slow convergence and high computational complexity. Initiated by the merits and shortcomings of the gradient-based algorithms and the evolutionary algorithms, we developed a new hybrid search methodology in which the genetic-type search is embedded into gradient-descent algorithms (such as the LMS algorithm). The new algorithm has the characteristics of faster convergence, global search capability, less sensitivity to the choice of parameters, and simple implementation. The basic idea of the new algorithm is that the filter coefficients are evolved in a random manner once the filter is found to be stuck at a local minimum or to have a slow convergence rate. Only the fittest coefficient set survives and is adapted according to the gradient-descent algorithm until the next evolution. As the random perturbation will be subject to the stability constraint, the filter can always minimum in a stable manner and achieve a smaller error performance with a fast rate. The article reviews adaptive IIR filtering and discusses common learning algorithms for adaptive filtering. It then presents a new learning algorithm based on the genetic search approach and shows how it can help overcome the problems associated with gradient-based and GA algorithms.

Proceedings ArticleDOI
17 Jun 1996
TL;DR: A digital predistorter with real time modeling of AM-AM and AM-PM characteristics of a power amplifier (PA) is presented, which is robust and efficient since no iterative procedure is needed, hence the convergence time is eliminated.
Abstract: When the signals resulting from linear modulation methods, like M-ary QAM, are passed through a nonlinear power amplifier, their fluctuating envelope causes distortion and spectral spreading. In order to avoid these effects, while maintaining both power and spectral efficiency, the use of linearization techniques is necessary. This paper presents a digital predistorter with real time modeling of AM-AM and AM-PM characteristics of a power amplifier (PA). The input and output lowpass equivalent complex envelopes of the amplifier are sampled, scaled and updated into a lookup table to provide the predistorted signal. An improvement of 45 dB of out-of-band power is obtained when simulating with Signal Processing WorkSystem (SPW). The proposed technique is robust and efficient since no iterative procedure is needed, hence the convergence time is eliminated.

Patent
26 Nov 1996
TL;DR: In this paper, a cross-coupled adaptive noise cancelling scheme is proposed, where the adaptive cross-talk filter is split into a prefilter section and an adaptive filter section, the sections using different inputs.
Abstract: Known is a so-called cross-coupled adaptive noise cancelling arrangement utilizing an adaptive noise filter and an adaptive cross-talk filter in a feedback loop for cancelling correlated noise at a primary signal input and reference input. The known cross-coupled ANC does not operate satisfactorily, particularly not for acoustic noise cancellation. This leads to reverberant-like sound singals, in particular in a typical office room with remote noise sources. A cross-coupled adaptive noise cancelling arrangement is proposed having a different configuration giving rise to a better performance. The adaptive cross-talk filter is split into a prefilter section and an adaptive filter section, the sections using different input signals. The prefilter section estimates the desired signal from the input signal of the noise cancelling arrangement, and the adaptive filter section has its input coupled to the output of the noise cancelling arrangement, a delay section being provided between the input and the output of the noise cancelling arrangement. In an embodiment, the prefilter section and the adaptive filter section are separate filters.

Proceedings ArticleDOI
07 May 1996
TL;DR: The problem of restoration of motion vector-fields computed by means of a standard block matching algorithm is addressed and an adaptive scheme based on the theory of vector-median filters is developed and results are discussed.
Abstract: In the field of video coding the issues of backward prediction and standards conversion have focused an increasing attention towards techniques for an effective estimation of the true interframe motion. The problem of restoration of motion vector-fields computed by means of a standard block matching algorithm is addressed. The restoration must be carried out carefully by exploiting both the spatial correlation of the vector-field, and the significance of the obtained vectors as measures of the reliability of the previous estimation step. A novel approach matching both the above requirements is presented. Based on the theory of vector-median filters an adaptive scheme is developed and results are discussed.

Journal ArticleDOI
TL;DR: A newly proposed detector is proposed, which assumes knowledge of the structure of the clutter covariance matrix, and is substituted by a proper estimate based on a set of secondary data vectors that achieves a constant false alarm rate and incurs an acceptable loss.
Abstract: The article addresses radar detection of coherent pulse trains embedded in spherically invariant noise with unknown statistics. Starting upon a newly proposed detector, which assumes knowledge of the structure of the clutter covariance matrix, we substitute the actual matrix by a proper estimate based on a set of secondary data vectors. Interestingly, the resulting detector achieves a constant false alarm rate with respect to the texture component of the clutter, and incurs an acceptable loss with respect to the case of a known covariance matrix.

Patent
23 Jan 1996
TL;DR: In this paper, a head-mounted display for displaying an image that matches a viewer's head movement has a head tracker, an eye tracker, and an adaptive filter for adaptively filtering the output of the head tracker.
Abstract: A head-mounted display for displaying an image that matches a viewer's head movement has a head tracker for detecting the viewer's head movement, an eye tracker for detecting the viewer's eye movement, and an adaptive filter for adaptively filtering the output of the head tracker in accordance with the output of the head tracker and the output of the eye tracker, and when tracker, and when the viewer is watching a particular object in the displayed image, the adaptive filter is set as a low-pass filter, and this and the output gain of the head tracker is lowered; in other cases, the adaptive filter is set as an all-pass filter, and this prevents minute shaking of the head from being reflected on the displayed image, while retaining image display response to head motion, and furthermore, this serves to keep the particular object from being shifted outside the field of view.