Showing papers on "Adaptive filter published in 1989"

An adaptive weighted median filter for speckle suppression in medical ultrasonic images

Abstract: A method for reducing speckle noise in medical ultrasonic images is presented. It is called the adaptive weighted median filter (AWMF) and is based on the weighted median, which originates from the well-known median filter through the introduction of weight coefficients. By adjusting the weight coefficients and consequently the smoothing characteristics of the filter according to the local statistics around each point of the image, it is possible to suppress noise while edges and other important features are preserved. Application of the filter to several ultrasonic scans has shown that processing improves the detectability of small structures and subtle gray-scale variations without affecting the sharpness or anatomical information of the original image. Comparison with the pure median filter demonstrates the superiority of adaptive techniques over their space-invariant counterparts. Examples of processed images show that the AWMF preserves small details better than other nonlinear space-varying filters which offer equal noise reduction in uniform areas. >

Adaptive IIR filtering

Abstract: An overview is presented of several methods, filter structures, and recursive algorithms used in adaptive infinite-impulse response (IIR) filtering. Both the equation-error and output-error formulations are described, although the focus is on the adaptive algorithms and properties of the output-error configuration. These parameter-update algorithms have the same generic form, and they are based on a prediction-error performance criterion. A direct-form implementation of the adaptive filters is emphasized, but alternative realizations such as the parallel and lattice forms are briefly discussed. Several important issues associated with adaptive IIR filtering, including stability monitoring, the SPR condition, and convergence, are addressed. >

An adaptive clustering algorithm for image segmentation

Abstract: A generalization of the K-means clustering algorithm to include spatial constraints and to account for local intensity variations in the image is proposed. Spatial constraints are included by the use of a Gibbs random field model. Local intensity variations are accounted for in an iterative procedure involving averaging over a sliding window whose size decreases as the algorithm progresses. Results with an eight-neighbor Gibbs random field model applied to pictures of industrial objects and a variety of other images show that the algorithm performs better than the K-means algorithm and its nonadaptive extensions. >

Multiple-Point Equalization in a Room Using Adaptive Digital Filters

Abstract: A method is presented for designing an equalization filter for a sound-reproduction system by adjusting the filter coefficients to minimize the sum of the squares of the errors between the equalized responses at multiple points in the room and delayed versions of the original electrical signal

Improved technique for design of perfect reconstruction FIR QMF banks with lossless polyphase matrices

Abstract: A technique is developed for the design of analysis filters in an M-channel maximally decimated, perfect reconstruction, finite-impulse-response quadrature mirror filter (FIR QMF) bank that has a lossless polyphase-component matrix E(z). The aim is to optimize the parameters characterizing E(z) until the sum of the stopband energies of the analysis filters is minimized. There are four novel elements in the procedure reported here. The first is a technique for efficient initialization of one of the M analysis filters, as a spectral factor of an Mth band filter. The factorization itself is done in an efficient manner using the eigenfilters approach, without the need for root-finding techniques. The second element is the initialization of the internal parameters which characterize E(z), based on the above spectral factor. The third element is a modified characterization, mostly free from rotation angles, of the FIR E(z). The fourth is the incorporation of symmetry among the analysis filters, so as to minimize the number of unknown parameters being optimized. The resulting design procedure always gives better filter responses than earlier ones (for a given filter length) and converges much faster. >

Applications of surface acoustic and shallow bulk acoustic wave devices

Abstract: Surface acoustic wave (SAW) device coverage includes delay lines and filters operating at selected frequencies in the range from about 10 MHz to 11 GHz; modeling with single-crystal piezoelectrics and layered structures; resonators and low-loss filters; comb filters and multiplexers; antenna duplexers; harmonic devices; chirp filters for pulse compression; coding with fixed and programmable transversal filters; Barker and quadraphase coding; adaptive filters; acoustic and acoustoelectric convolvers and correlators for radar, spread spectrum, and packet radio; acoustooptic processors for Bragg modulation and spectrum analysis; real-time Fourier-transform and cepstrum processors for radar and sonar; compressive receivers; Nyquist filters for microwave digital radio; clock-recovery filters for fiber communications; fixed-, tunable-, and multimode oscillators and frequency synthesizers; acoustic charge transport (ACT); and other SAW devices for signal processing on gallium arsenide. Shallow bulk acoustic wave (SBAW) device applications include gigahertz delay lines, surface-transverse-wave resonators employing energy-trapping gratings and oscillators with enhanced performance and capability. >

Assessment of air-to-air missile guidance and control technology

Abstract: Current air-to-air missile guidance and control technology is assessed. Areas explored include target state estimation, advanced guidance laws, and bank-to-turn autopilots. The assumptions, benefits, and limitations of recent applications of nonlinear filtering, adaptive filtering, modern control, adaptive control, dual control, differential game theory, and modern control design techniques to the air-to-air missile problem are discussed. >

Optical novelty filters

Abstract: A novelty filter detects what is new in a scene and may be likened to a temporal high-pass filter. The current status of optical novelty filters and related devices, based upon four-wave mixing and two-beam coupling in photorefractive media, is reviewed. A detector that shows only what is not new, a monotony filter, may be likened to a temporal low-pass filter. Demonstrations of high- and low-pass and bandpass temporal image filters are then discussed. An analytical treatment of the two-beam coupling devices is given in a Laplace transform framework in the undepleted pump approximation assuming plane wave inputs. This allows a unified treatment of the various filter characteristics. >

Selective active cancellation system for repetitive phenomena.

Abstract: A cancellation system (10) including a processor (24) having single adaptive filters (44, 46) adapting its filtering characteristic as a function of a phenomena signal and phenomena timing signal and a phase circuit to maintain the adapting of the filtering characteristics within 90 degrees phase of the phenomena signal. The phase circuit has the capability to measure the delays of the processor and the environment. The system (10) is fast enough to use only an error sensor and can be manually or automatically tuned.

Performance of an adaptive detection algorithm; rejection of unwanted signals

Abstract: The analysis of an adaptive detection algorithm described previously by the author (1985, 1986) is extended. Previously, the performance was evaluated for the case of a signal corresponding exactly to the steering vector used in the derivation of the algorithm. Here the performance for signals arriving from other directions is evaluated. It is shown that these signals are rejected much more strongly than would be suggested by the sidelobe levels of the adapted patterns themselves. >

Bit-serial realizations of a class of nonlinear filters based on positive Boolean functions

Abstract: It is shown that the function of a stack filter can be realized in k-step recursive use of one binary processing circuit. The time-area complexity of the proposed filter is O(k) as compared with O(2/sup k/) for stack filters. The proposed digital realizations are simple and modular in structure, and suitable for VLSI implementation. Analog/digital (A/D) hybrid realizations have the advantage that there is no need for an A/D converter array when the original signals come from an integrated sensor array. An experimental digital rank-order filter with a window size of three and arbitrary number of input bits is designed and implemented in a 3- mu m double-metal polysilicon gate CMOS process. The chip has been fabricated and measurement results are correct with a clock frequency of up to 110 MHz. >

A design technique for variable digital filters

Abstract: In some applications the frequency characteristics of a filter may be required to change during the course of signal processing. This requirement can be satisfied by filters with coefficients that are directly computable from the specified spectral parameters. Such filters are referred to as variable filters. A design technique for variable filters is proposed. The filter coefficients are expressed as analytical functions of the frequency specifications by using a curve-fitting technique. Several examples are presented to illustrate the method. >

Adaptive line enhancement by using an IIR lattice notch filter

Abstract: Two simple methods for retrieving a single sinusoid corrupted with noise are proposed. They are based on the lattice form realization of an adaptive infinite-impulse-response (IIR) notch filter. The IIR filter is a cascade of second-order all-pole and all-zero filters, and the coefficients of the finite-impulse-response (FIR) section are adapted. The proposed algorithms keep the poles of the filter inside the unit circle. The computer simulation results show that the algorithms have considerable potential in adaptive notch filter applications, especially when the input signal-to-noise ratio is low. >

Automatic track formation in clutter with a recursive algorithm

Abstract: A recursive algorithm for forming tracks in a cluttered environment is presented. The approach combines the interacting multiple model algorithm with the probabilistic data association filter. The track formation is accomplished by considering two models: one is the true target, with a certain probability of detection P/sub D/; the other is an unobservable target (or no target) with the same model as the former except that P/sub D/=0. The latter represents either a true target outside the sensor coverage or an erroneously hypothesized target. Assuming that the clutter measurements are uniformly distributed, the algorithm yields the true target probability of a track; i.e. it can be called intelligent, since it has a quantitative assessment of whether it has a target in track. The algorithm is useful for low signal-to-noise-ratio situations where the detection threshold has to be set low in order to detect the target, leading to a high rate of false alarms. >

Performance analysis of frequency-domain block LMS adaptive digital filters

Abstract: The performance of the frequency-domain block least-mean-square (FBLMS) adaptive digital filters, whose filter weights are updated efficiently using the fast Fourier transform, is investigated. In particular, the convergence of the unconstrained FBLMS algorithm with reduced complexity, which is obtained by removing the constraint that has been known to be required in adjusting the frequency-domain weights based on overlap-save sectioning, is analyzed. The performance of the self-orthogonalizing FBLMS algorithm with improved convergence speed, in which different convergence factors normalized by frequency-domain power estimates are used for different frequency components of the weights, is also studied. >

Conjugate gradient techniques for adaptive filtering

Abstract: The technique of conjugate gradients is applied to the adaptive filtering problem. The method provides convergence comparable to that of RLS (recursive-least-squares) schemes and has a computational requirement that is intermediate between the LMS (least-mean-square) and the RLS methods. It does not suffer from any known stability problems. >

On the design of FIR filters by complex Chebyshev approximation

Abstract: The long-standing problem of approximating a complex-valued desired function with a finite impulse-response (FIR) filter is considered. It is formulated as an equalization to be solved using complex-valued filters. The proposed algorithm deals directly with the complex error function, which depends linearly on the coefficients of the filter to be designed. The magnitude of this error function is minimized in the Chebshev sense using a generalization of the Remez exchange algorithm. The method can be used to design complex- or real-valued-selective systems as well. The well-known design of optimal FIR filters with linear phase is included here as a special case. >

Ll-filters-a new class of order statistic filters

Abstract: The Ll-filters are introduced to generate the order statistic filters (L-filters) and the nonrecursive linear, or finite-duration impulse-response (FIR), filters. Such estimators are particularly effective filtering signals that do not necessarily follow Gaussian distributions. They can be designed to restore one-dimensional or multidimensional signals corrupted by noise of impulsive type. Such filters are appealing since they are suitable for being made robust against the presence of spurious outliers in the data. >

Adaptive beamforming for noise reduction

Abstract: The invention provides an adaptive noise cancelling apparatus which operates to overcome a problem encountered in conventional noise cancelling circuitry when the signal-to-noise ratio at the sensor array is high--to wit, that the target signal is degraded, leading to poorer intelligibility. An apparatus constructed in accord with the invention selectively inhibits the adaptive filter from changing its filter values in these instances and, thereby, prevents it from generating a noise-approximating signal that will degrade the target component of the output signal.

Measurement and adaptive suppression of acoustic feedback in hearing aids

Abstract: The authors describe a technique for making in situ measurements of the acoustic feedback path transfer function and present results demonstrating the effect of changes in the acoustic environment on this transfer function. Three methods of feedback suppression are explored: time-varying delay, adaptive inverse filtering, and adaptive feedback cancellation. It is concluded that the latter approach is the most successful, increasing the maximum gain the hearing aid can deliver without acoustic feedback by 6-10 dB. This increased gain can provide a benefit for moderately-impaired listeners. >

Adaptive IIR filtering using parallel-form realizations

Abstract: Several parallel-form adaptive IIR (infinite impulse response) filters are presented, including a frequency-domain implementation based on the discrete Fourier transform and a recursive frequency-sampling structure. The performance of the frequency-domain adaptive IIR filter is investigated in a system identification application, which includes an analysis of its modeling capabilities and a discussion of the mean-square-error performance surface. Computer simulation results are presented to illustrate the robust convergence properties of the adaptive algorithm and to demonstrate the stability of the filter. >

Theory of order statistic filters and their relationship to linear FIR filters

Abstract: Necessary and/or sufficient conditions on both the filter coefficients and the signal process are derived in order that nonrecursive order statistic (OS) and linear filtering are equivalent operations. The results indicate that an understanding of OS filters hinges on a better understanding of the properties of signals containing logically monotonic components. The results extend a number of previous theories characterizing the well-known median and ranked-order filters to a broader class of filters and input signals. >

Programmable multichannel hearing aid with adaptive filter

Abstract: A hearing aid is programmable with dual-tone multiple-frequency signals, received through the hearing aid microphone, to adjust operating coefficients of signal conditioning circuitry in the aid. A DTMF receiver filters and detects DTMF tone pairs into digital words provided to a controller for decoding, some of the digital words representing programming instructions and others representing data. In accordance with the instructions, the controller conveys the data to memory operatively associated with a plurality of control ports to the signal conditioning circuitry, with operating coefficients of the conditioning circuitry determined by the contents of the memory.

Full-duplex digital speakerphone

Abstract: A full-duplex digital speakerphone 10 includes a transmit signal path having an output coupled to a telephone trunk and a receive signal path having an input coupled to the telephone trunk and an output coupled to a loudspeaker. The speakerphone further includes a room echo cancellation adaptive filter 56 and a trunk echo cancellation adaptive filter 66. Serially coupled within the transmit signal path is a selective suppression block 50 for suppressing a component of a Mu-Law or an A-Law quantization error signal. A second selective suppression block 52 is serially coupled within the receive signal path. Suppression of non-linearities due to Mu-Law or A-Law signal conversion is also accommodated by providing a non-linear signal processing block 40 at an input to an adaptive filter and an optional non-linear signal processing block at an output of the adaptive filter. Each of the blocks emulates and compensates for signal converter non-linearity. The speakerphone facilitates adaptive filter coefficient initialization by beginning a call in a half-duplex mode and switching to full-duplex when filter coefficients are adapted. The speakerphone also has a variable adaptation step size which is a function of a short-term estimate of signal power within the associated transmit or receive signal paths.

Alternate realizations to adaptive IIR filters and properties of their performance surfaces

Abstract: It is shown how different structures of an adaptive filter lead to a change in the characteristics of the corresponding error surface and, consequently, to a change in the corresponding convergence rate and minimum mean-square error. Alternate realizations of adaptive infinite impulse response (IIR) filters are presented, and some properties of their performance surfaces are found through mathematical analysis. A parallel-form realization of adaptive IIR filters is introduced, and the behaviors of the recursive least-mean-square algorithm for this structure and for the direct form realization are compared. A general theory based on an analysis of stationary points is presented. This general result is then specialized for parallel and cascade realizations. >

Orthonormal ladder filters

Abstract: A state-space structure for the realization of arbitrary filter transfer-functions is presented. This structure should prove useful where integrators are the basic building blocks such as in transconductance-C, MOSFET-C, or active-RC filters. The structure is derived from a singly terminated LC ladder and has the characteristics that it is always scaled for optimum dynamic range and its integrator outputs are orthogonal. For this reason, the resulting realizations are called orthonormal ladder filters. Since dynamic range scaling is inherent to the proposed structure, it is felt that this design technique may be most useful in programmable or adaptive filters. The sensitivity and dynamic range properties of an orthonormal ladder filter are shown to be comparable in performance to the equivalent properties obtained from a cascade of biquads. >

Statistical Analysis of Median Subtraction Filtering with Application to Point Target Detection in Infrared Backgrounds

Abstract: The nonstationarity of infrared interference backgrounds which prevents the implementation of the usual optimum linear filtering techniques makes clutter suppression signal processing for point target detection in infrared surveillance systems a challenging and difficult problem. Hence, more robust filtering schemes are sought which will perform well in structured backgrounds where the underlying probability distribution defining that structure is not well known or characterized. This paper investigates a promising candidate spatial filter for point-like feature detection in infrared systems. The technique, known as median subtraction filtering, is a robust, nonlinear, order statistic type filter which exhibits highpass filter characteristics without the usual ringing associated with linear highpass filters. A quantitative analysis of the statistical properties of the median subtraction filter is presented, including analytic expressions for the output distribution of the filter (thus analytic expressions for the probability of detection and probability of false alarm), its autocorrelation function and spectral density function. Performance results of a signal processing simulation comparing a median subtraction filter with an adaptive linear filter of the LMS type using actual infrared video as input are also included.

A new convergence factor for adaptive filters

Abstract: It is proposed that the convergence factor mu in the adaptive filter can be made time-varying according to the gradient of the performance surface. Computer simulations show that when a suitable damping parameter, alpha , is used, the algorithm possesses a fast convergence rate and yields very small misadjustment. The algorithm works well under nonstationary environments, in sharp contrast with the two-stage method. >

Edge-adaptive Kalman filtering for image restoration with ringing suppression

Abstract: The authors extend the two-dimensional (2-D) linear space-invariant (LSI) reduced update Kalman filter (RUKF) to edge-adaptive space-invariant restoration of noisy and blurred images using a decision-directed approach. The edge-adaptive RUKF was motivated by the need to suppress the ringing artifacts caused by LSI processing. The authors show that ringing artifacts can be suppressed to a great extent by using multiple image models that provide a better match to local edge orientation. The maximum a posteriori probability decision procedure developed for model selection at each pixel can be used with other 2-D Kalman filtering algorithms as well. >

Adaptive IIR algorithms based on high-order statistics

Abstract: Recursive estimation algorithms are derived for moving-average and autoregressive moving-average processes. These algorithms can be used for adaptive infinite impulse response (IIR) filtering of non-Gaussian processes. The behavior of these algorithms is illustrated by extensive numerical examples. >