Showing papers on "Kernel adaptive filter published in 1984"

Adaptive notch filtering for the retrieval of sinusoids in noise

Abstract: In this paper, an adaptive notch filter is developed (employing a frequency domain and time domain analysis) for the enhancement and tracking of sinusoids in additive noise, colored or white. The notch filter is implemented as a constrained infinite impulse response filter with the constraint enforced by a single parameter termed the debiasing parameter. The resulting notch filter requires few parameters, facilitates the formation of the desired band rejection filter response, and also leads to various useful implementations (cascade, parallel). For the adaptation of the filter coefficients, the stochastic Gauss-Newton algorithm is used. The convergence of this updating procedure is established by studying the associated differential equation. Also, it is shown that the structure present in the problem enables truncation of the gradient, thereby reducing the complexity of adapting the filter coefficients. Simulation results are presented to substantiate the analysis, and to demonstrate the potential of the notch filtering technique.

Two-input crosstalk-resistant adaptive noise canceller

Abstract: A two-input crosstalk-resistant adaptive noise canceller receives a primary input signal including a desired speech signal portion and an undesired noise signal portion and also receives a reference input signal having a reference noise input portion and a crosstalk speech portion. The canceller has first and second summer means and first and second adaptive filter means. The first summer means provides a canceller output signal which is the difference between the primary input signal and the first adaptive filter output signal. The canceller output signal is applied to the reference input of the second adaptive filter and to one of a pair of error-control inputs of the first adaptive filter. The second error-control input of the first adaptive filter is provided by the signal at the output of the second adaptive filter, which receives a single error-control input signal from the output of the second summer means. The second summer provides an output signal which is the difference between the reference input signal and the second adapter filter output signal. With the correlation bias between the desired primary input (speech) signal and the crosstalk (speech) signal in the reference input substantially reduced, the canceller output signal is then related substantially only to the primary input desired signal.

An adaptative, nonlinear edge-preserving filter

Abstract: An adaptative filter whose main feature is to preserve edges and impulses present in the signal is analyzed by the computation of the mean-square error (MSE) of its output sequence. The filter in its more general form is highly nonlinear, resembling the M-type estimators used in robust statistics. A simplified form used here allows the exact computation of the MSE when the filter length is finite. This MSE can be compared to the ones obtained for a median filter and a mean filter. It is shown that for a wide range of the filter and signal parameters such as filter length, edge heights, and impulse width, the performance of the filter proposed in this paper is superior to the other filters mentioned above. An additional advantage of the simplified version of the filter is that in most cases, its computation amounts to a linear adaptative averaging. This contrasts with the amount of calculation required to implement the median filter and any other filter based on the order statistics of the measured samples.

Analysis and performance evaluation of an adaptive notch filter

Abstract: An adaptive notch filter is derived by using a general prediction error framework. The proposed infinite impulse response filler has a special structure that guarantees the desired transfer characteristics. The filter coefficients are updated by a version of the recursive maximum likelihood algorithm. The convergence properties of the algorithm and its asymptotic behavior are discussed, and its performance is evaluated by simulation results.

Adaptive signal processing for adaptive control

Abstract: A few of the well established methods of adaptive signal processing are modified and extended for application to adaptive control. An unknown plant will track an input command signal if the plant is preceded by a controller whose transfer function approximates the inverse of the plant transfer function. An adaptive inverse modeling process can be used to obtain a stable controller, whether the plant is minimum or non-minimum phase. No direct feedback is involved. However the system output is monitored and utilized in order to adjust the parameters of the controller. The proposed method is a promising new approach to the design of adaptive control systems.

Performance of minimum-variance deconvolution filter

Abstract: Recently, we observed zero phase and undershoot patterns in data processed by a minimum-variance deconvolution (MVD) filter. These observations motivated a careful analysis of the MVD filter, which, as we demonstrate in this paper, explains both the zero phase and undershoot patterns. This analysis also connects the MVD filter with the well-known prediction-error filter [6], and Berkhout's two-sided least-squares inverse filter [7]. We show that the performance of the MVD filter depends heavily on the bandwidth of the source wavelet and signal-to-noise ratio, and only slightly on data length.

Adaptive Input Filter Compensation for Switching Regulators

Abstract: An input filter is frequently employed between a switching regulator and its power source. However, its presence often results in degradation of dynamic performances and stability. The detrimental interaction is between an input filter and a switching regulator and is a function of the input filter parameters and also of the supply voltage. An earlier paper presented an analysis and design procedure aimed at developing a feed-forward loop to cancel this undesirable interaction. The feed-forward design is extended here to encompass a scheme that automatically accounts for changes in the supply voltage; the result is an adaptive compensation that tracks the input voltage variations. Experimental results are presented that confirm the adaptive nature of the design.

Adaptive adjustment of receiver for distorted digital signals

Abstract: The paper presents the results of an initial feasibility study into a novel technique for the adaptive adjustment of the receiver in a digital data-transmission system, operating with additive noise and severe inter-symbol interference in the received signal. The technique is an iterative process and can be used for the adjustment of the linear feedforward transversal filter that is employed ahead of a near-maximum-likelihood detector, and at the same time for the estimation of the sampled impulse response of the channel and filter, to give the information on the received signal needed by the detector. The latter two operations are equivalent to the adjustment of the feedforward and feedback transversal filters, respectively, in the corresponding nonlinear (decision-feedback)equaliser. The equaliser is, of course, a degenerate form of a near-maximum-likelihood detector, being obtained when the latter is reduced to its simplest possible form. The adaptive system operates directly on the estimate of the sampled impulse response of the channel, that must be provided at the receiver, and it requires no other input signals. It employs a root-finding algorithm that determines some of the roots (zeros) of the z-transform of the sampled impulse response of the channel. It then uses a knowledge of these roots to determine the tap gains of the linear feedforward transversal filter and to form an estimate of the sampled impulse response of the channel and filter. The technique can exploit the high tolerance to signal distortion of a near-maximum-likelihood detector in order to reduce the amount of processing of the received signal that is carried out by the adaptive filter to a level appreciably below that required by a conventional nonlinear equaliser. Thus a more cost-effective design of the receiver can be obtained. The paper describes the method of operation of two versions of the adaptive system and presents the results of computer-simulation tests over four different channels, showing both the rate and accuracy of convergence of the iterative process in each case.

Adaptive comb filter.

Abstract: Various filter circuits for a processing digitized color television signals are disclosed. Particularly, there are disclosed several embodiments of a luminance/chrominance signal separating filter (11) with which separated, digitized luminance and chrominance signals are derived with a minimum amount of interference therebetween by determining the direction from a given point in which there is a minimum amount of change in the digitized image signal. Also, there is disclosed a subnyquist sampling filter which operates upon this same principle.

Adaptive acoustooptic filter

Abstract: A new adaptive filter utilizing acoustooptic devices in a space integrating architecture is described. Two configurations are presented; one of them, suitable for signal estimation, is shown to approximate the Wiener filter, while the other, suitable for detection, is shown to approximate the matched filter.

Detection of multiple sinusoids using a parallel ALE

Abstract: This paper introduces an Adaptive Line Enhancer (ALE) whose parallel structure enables the detection and enhancement of multiple sinusoids. A function describing the performance surface is derived for the case where several line signals are buried in white noise. A steepest descent adaptive algorithm is derived, and simulations are used to demonstrate its performance.

Delay lattice filter for radar doppler processing

Abstract: An adaptive filter for enhancing the discrimination of targets from clutter and noise and suitable for use in a pulse doppler radar signal processor which processes successive echo pulse period signalling in accordance with range cell samples is disclosed. One embodiment of the filter has a delayed lattice configuration including a plurality of cascadedly coupled lattice stages, each adapted to operate on the range cell samples of first and second complex signal inputs. The adaptive filter embodiment provides rapid and low cost updating of the lattice stage weighting coefficients so that varying clutter spectrums may be effectively dealt with. Moreover, the lattice filter embodiment is insensitive to average clutter motion and to transmitter phase and gain instabilities. It further permits the use of variable interpulse period operation in radars that are unambiguous in range. Furthermore, the lattice filter embodiment adapts to and whitens the actual clutter spectrum being received by the radar and not some model spectrum that may be quite inaccurate.

Suppression of Narrow-Band Interference in a PN Spread-Spectrum Receiver Using a CTD-Based Adaptive Filter

Abstract: Analytical results have shown that adaptive filtering can be a powerful tool for the rejection of narrow-band interference in a spreadspectrum receiver. However, the complexity of adaptive filtering hardware has hindered the experimental verification of these results. This paper describes a new adaptive filter architecture for implementing the Widrow-Hoff LMS algorithm while using only two multipliers regardless of filter order. This hardware simplification is achieved through the use of a burst processing technique. A 16-tap version of this adaptive filter constructed using charge-transfer devices (CTD's) is used to suppress a single tone jammer in a direct sequence spread-spectrum receiver. Probability of error measurements demonstrating the effectiveness of the adaptive filter for suppressing the single tone jammer along with simulation results for the optimal Weiner-Hopf filter are presented and discussed.

Filter for determining target data

Abstract: In this filter, optimum filter coefficients are determined from widely scattered measurement values, for example bearings, in an iterative signal processing circuit. The filter coefficients and the measurement values are used for driving an accumulation circuit which determines correction values for an initial estimate of the target data. According to the invention, the filter is improved by additional multiplication circuits for determining the coefficients for the dynamic target data, that is to say the velocity components. Such filters are used in solving navigation tasks, particularly the passive determination of position and motion data of target vehicles.

A comparative study of the LMS adaptive filter versus generalized correlation method for time delay estimation

Abstract: This paper provides a comparison of the LMS adaptive filter versus conventional Generalized Correlation (GC) methods of time delay estimation in terms of their mean-square-error performance. The treatment is restricted to broadband stationary inputs with finite observation time without a priori knowledge of the processor input statistics. The time delay estimator probability distribution, variance, and error probability are derived for the LMS adaptive filter approach. Further, a performance index is given which is optimized with respect to choice of step size. The simulation results presented indicate that without a priori knowledge of the input statistics, both approaches yield similar sub-optimal results. On the other hand, optimal processing of the adaptive filter weights can yield an estimator with variance similar to that of the minimum variance GC method which approaches the Cramer-Rao Lower Bound.

New method for generating two-variable VSHPs and its application in the design of two-dimensional recursive digital filters with prescribed magnitude and constant group delay responses

Abstract: In the paper a method is presented for the design of 2-D stable recursive digital filters satisfying prescribed magnitude and constant group delay responses. This technique uses the properties of positive definite matrices and their application in generating 2-variable Very Strictly Hurwitz Polynomials (VSHPs), which will be assigned to the denominator of a 2-D analogue reference filter. Bilinear transformations are then applied to the transfer function of the derived 2-D analogue reference filter to obtain the discrete version of the 2-D filter. Parameters of the discrete 2-D filter can be used as the variables of optimisation to minimise the leastmean-square error between the desired and designed magnitude and group delay responses of the filter. To show the usefulness of the technique, an example is given.

Filter for data processing

Abstract: Improved Filter for Data Processing Abstract An imaging method and apparatus having a new and improved data filter. In one application of the inven-tion computed tomography number inaccuracies are avoided by use of a new filter function derived from discrete points of a truncated spatial domain convolution filter. The points from the truncated convolution filter are fourier transformed to yield a ramp filter with ripple in the spatial frequency domain. Data from a CT scan is filtered with this new filter function and back projected to produce images that do not exhibit CT number inaccuracies.

Optimal all-pole filter design based on discrete prolate spheroidal sequences

Abstract: A new constrained optimization method for all-pole digital filter design is presented. The design philosophy employed minimizes a function of the area between the ideal low-pass filter response in the passband and the actual filter response subject to a quadratic constraint which ensures filter realizability. It is shown that unique solutions are obtained which are related to eigenvectors of a Toeplitz matrix whose elements form a scaled discrete prolate spheroidal wave sequence (DPSS). It is therefore possible to exploit the properties of DPSS and discrete prolate spheroidal wave functions (DPSWF's) to reduce the filter design effort. The ratio of passband energy to total energy over the entire filter bandwidth is optimal for these designs.

A time-domain adaptive algorithm for rapid convergence

Abstract: A time-domain adaptive LMS algorithm is presented which has, theoretically, the fastest convergence rates. The algorithm requires o(N2) operations where N is the length of the adaptive filter. It is shown that this algorithm is equivalent to the transform-domain adaptive algorithm with the optimum convergence rates proposed by Narayan et al. However the present algorithm does not require Karhunen-Loeve transforms for its implementation. It is also shown that the algorithm can be implemented with a complexity of o(mN) operations if the input process to the adaptive filter can be modeled as an autoregressive process of order m.

A comparison of image filtering algorithms

Abstract: This paper compares four image filtering algorithms on common data sets for various signal to noise ratios and white Gaussian noise. The algorithms are the median filter, the Wallis filter, the reduced update Kalman filter, and a multiple model, decision-directed filter. This comparison produces some surprising results from both a subjective (visual error) and a mean square error (MSE) viewpoint.

Direct design of recursive digital filters based on a new stability test

Abstract: In this paper we present an alternative approach to the direct design of 1-D recursive digital filters satisfying prescribed magnitude specifications with or without constant group delay characteristic. This method uses an iterative method to calculate the coefficients of the filter's transfer function and guarantees the stability of the designed filter using a new stability test reported by Ramachandran and Gargour. To illustrate the usefulness of the technique, examples are given.

Nonstationary 2-D recursive restoration of images with signal-dependent noise

Abstract: A nonstationary 2-D recursive image restoration filter that uses a nonstationary mean, nonstationary variance (NMNV) image model and minimizes the local mean square error is developed. The 2-D recursive filter adapts itself to the local image statistics and is able to do space-variant processing. The NMNV image model has a simple dynamic representation which simplifies the filter structure considerably. However, the optimal recursive filter still requires extensive computation. A suboptimal approach that uses a reduced update concept is proposed to reduce the computational efforts. With some modifications, this nonstationary 2-D recursive filter is extended to a class of uncorrelated, signal-dependent noise such as multiplicative noise and Poisson noise. The explicit filter structures and simulation results for images degraded by these signal-dependent noises are presented.

N-path digital filters

Abstract: According to the sampling theorem, a faster sampling rate is required in order to process signals containing high frequency components. The processing rate is restricted by the highest operating speed of devices available. This paper presents the design of N-path parallel processing technique which would overcome the speed limitation of present devices. The transfer function of N-path digital filter is shown to be H(zN), where H(z) is the transfer function of each component filter block. This implies that the overall magnitude response of N-path digital filter is a frequency scaled version of that of component filter. In the proposed paper, a scheme to cancel out the unwanted passbands by cascading several N-path filters is first discussed. Then the design procedure of N-path filter from given specification is illustrated using simple example.

A hybrid system for the reconstruction of a smooth function from its samples

Abstract: The long-standing problem of reconstructing a function from its samples is considered again. Assuming a sequence of oversampled values, a set of appropriate idealized reconstruction filters can be defined, which do not suffer from instability or slow convergence. The realization — a cascade of a nonrecursive digital filter, D/A-converter, and a fixed/analog smoothing filter — demands the design of the digital filter for the increase of the sampling rate. The design of this nonrecursive filter is the purpose of this paper. Approximations in the frequency as well as in the time domain are presented.

Analysis of a new nonlinear filter and tracking methodology (Corresp.)

Abstract: A recursive nonlinear filter and tracking methodology is developed for a class of partially observable processes with an approximating model which is linear in the unobservable states and initially has the unobservables conditionally Gaussian with respect to the observations. The usual model smoothness is not required, and applications to simulated tracking problems show the filter to be considerably more accurate than the modified second-order filter which in a general sense includes the extended Kalman filter.

A multi-signal bus architecture for FIR filters with single bit coefficients

Abstract: An architecture for FIR filter with binary coefficients based on partitioning the filter transfer function is investigated. Two computational complexity measures, corresponding to VLSI implementation and to the number of adders are minimized with respect to a partition parameter. One of the optimal architectures is shown to require O(N/\logN) adders instead of N . This is attributed to the fact that the proposed architecture removes, in an optimal fashion, redundancies shown to inherently exist in the filter structure. This is achieved by precomputing from the input signal other signals that are most commonly needed through the filter structure in what might be called a multisignal bus architecture.

Adaptive algorithms that restore signal properties

Abstract: This paper introduces the concept of designing adaptive filtering algorithms to exploit the presence of some invariant property possessed by a signal of interest. If this invariant property is disturbed by the interference or dispersion which degrades the signal's quality, and if the disturbance can be sensed, then it can be used to guide an adaptive algorithm. Certain analytic requirements on this type of algorithm are discussed as well as their relation to well-known least squares and MSE algorithms.