Cancellation Filter Research Articles

A Modified Filtered-X LMS Algorithm for Active Control of Periodic Noise with On-Line Cancellation Path Modelling

The filtered-x LMS algorithm (FXLMS) has been successfully applied to the active control of periodic and random noise and vibration. This paper presents a modified algorithm for active control of periodic noise based on the FXLMS algorithm which uses random noise for on-line cancellation path transfer function (CPTF) estimation. In the proposed algorithm, another two short adaptive filters are introduced. One is an adaptive noise cancellation filter, which is used to improve the convergence speed of the CPTF modelling filter in the presence of very large amplitude primary noise by cancelling the component of the error signal that is correlated with the primary noise. The other is an adaptive estimator, which is used to re-estimate the obtained CPTF (long FIR filter estimated by random noise) with a short FIR filter by using the periodic reference signal as the input. The traditional FXLMS algorithm is then used with the shortened FIR filter to filter the reference signal, thus providing significant processing flexibility in practical situations where the primary path transfer function changes much faster than the CPTF. Simulation results demonstrate the effectiveness of the proposed algorithm.

Analysis of Different Low Complexity Nonlinear Filters for Acoustic Echo Cancellation

Linear filters are often employed in most signal processing applications. As a matter of fact, they are well understood within a uniform theory of discrete linear systems. However, many physical systems exhibit some nonlinear behaviour, and in certain situations linear filters perform poorly. One case is the problem of acoustic echo cancellation, where the digital filter employed has to identify as close as possible the acoustic echo path that is found to be highly nonlinear. In this situation a better system identification can be achieved by a nonlinear filter. The problem is to find a nonlinear filter structure able to realize a good approximation of the echo path without any significant increase of the computational load. Conventional Volterra filters are well suited for modelling that system but they generally need too many computational resources for a real time implementation. In this paper we consider some low complexity nonlinear filters in order to find out a filter structure able to achieve performances close to those of the Volterra filter, but with a reduced increase of the computational load in comparison to the linear filters commonly employed in commercial acoustic echo cancellers.

Control of feedback in hearing aids-a robust filter design approach

A bound on the variability of the feedback path is employed in the design of fixed FIR hearing aid filters that are robust to the specified variability, thus avoiding instability and howling in everyday use. A design example is presented for a linear gain hearing aid filter with a given maximal mismatch of the feedback cancellation filter.

Multiple period estimation and pitch perception model

The pitch of a periodic sound is strongly correlated with its period. To perceive the multiple pitches evoked by several simultaneous sounds, the auditory system must estimate their periods. This paper proposes a process in which the periodic sounds are canceled in turn (multistep cancellation model) or simultaneously (joint cancellation model). As an example of multistep cancellation, the pitch perception model of Meddis and Hewitt (1991a, b) can be associated with the concurrent vowel identification model of Meddis and Hewitt (1992). A first period estimate is used to suppress correlates of the dominant sound, and a second period is then estimated from the remainder. The process may be repeated to estimate further pitches, or else to recursively refine the initial estimates. Meddis and Hewitt's models are spectrotemporal (filter channel selection based on temporal cues) but multistep cancellation can also be performed in the spectral or time domain. In the joint cancellation model, estimation and cancellation are performed together in the time domain: the parameter space of several cascaded cancellation filters is searched exhaustively for a minimum output. The parameters that yield this minimum are the period estimates. Joint cancellation is guaranteed to find all periods, except in certain situations for which the stimulus is inherently ambiguous.

Qualitative and quantitative results from a speech enhancement scheme assessed by hearing-impaired subjects

A multi-microphone sub-band adaptive system for binaural preprocessing of speech signals for potential processing in future hearing aids has been investigated. Results are presented from both quantitative and qualitative assessments of the performance of the processing scheme as recorded from hearing-impaired subjects. The quantitative assessment is based on intelligibility testing of the algorithm using real-room recordings, T60=0.3 s, with multi-talker babble as the unwanted noise source. This evaluation has been conducted by using the four-alternative auditory feature test developed by Foster and Haggard [J. Br. Audiol. 21, 165–174 (1987)]. A corresponding mean opinion score on speech quality from each test subject provides the qualitative analysis. A response time measure was included with the qualitative measure. The processing scheme uses the least mean squares (LMS) [S. D. Sterns and R. A. David, Signal Processing Algorithms (Prentice–Hall, Englewood Cliffs, NJ, 1988)] adaptive noise cancellation algorithm in frequency-limited subbands. The inputs from each microphone are split into 16 contiguous subbands using a cochlear distribution according the function provided by Greenwood [J. Acoust. Soc. Am. 87, 2592–2605 (1990)]. Each frequency-limited subband is processed using a LMS adaptive noise cancellation filter operating in an intermittent or continuous mode depending on input signal characteristics. The results show a statistically significant and practically valuable improvement in both intelligibility and perceived speech quality using the proposed scheme.

Higher-order time-varying allpass filters for signaldecorrelation instereophonic acoustic echo cancellation

A new technique is presented for decorrelating the input signals in stereophonic systems by means of time-varying allpass filters. The controllable and almost linear phase response of higher-order allpass filters is exploited in this context and a particular type of time variation is used to vary the parameters of such filters. Simulation results are presented based on real stereophonic signals and supported by subjective listening tests.

A fast recursive-least-squares adaptive notch filter and its applications to biomedical signals.

A fast recursive-least-squares (FRLS) adaptive notch filter (ANF) for cancellation of sinusoidal interference from recorded biomedical signals is investigated. The FRLS ANF is derived by making an approximation to the conventional recursive-least-squares (RLS) ANF for computation economy. It outperforms the commonly adopted least-mean-squares (LMS) ANF, demonstrating a rapid and bandwidth-insensitive initial convergence. A novel application of the FRLS ANF is for the elimination of the tonal artefact in distortion product otoacoustic emission (DPOAE) signals.

Acoustic echo cancellation in an integrated audio and telecommunication system

Robust acoustic echo cancellation in a single-channel integrated audio and intercom system is provided by adapting echo cancellation filters in accordance with an optimized autocorrelation matrix. This is carried out in a modified FIR LMS filter in which the adaptation regressor signal is formed by a combination of one or more of the received voice signal, the received audio signal, and/or a random noise signal. In a SISO system, it is usually desirable to shelter the regressor signal from tonal components such as voice signals. In a multiple-channel system, it is usually desirable to shelter regressor signals for a particular channel from acoustic components that are likely to be correlated to acoustic components in other parts of the system and are likely to affect that particular channel. In multi-channel applications, it is therefore usually desirable to shelter regressor signals from audio signals.

Impulse noise removal using polynomial approximation

A novel filtering algorithm is presented to restore images cor- rupted by impulsive noise. As a preprocessing procedure of the noise cancellation filter, an improved impulse detector is used to generate a binary flag image, which gives each pixel a flag indicating whether it is an impulse. This flag image has two uses: (1) a pixel is modified only when it is considered as an impulse; otherwise, it is left unchanged, and (2) only the values of the good pixels are employed as useful information by the noise cancellation filter. To remove noises from the corrupted image, we propose a new filter called a polynomial approximation (PA) filter, which is developed by modeling a local region with a polynomial that can best approximate the region under the condition of least squared error. Furthermore, an adaptive approach is introduced to automatically deter- mine the orders of the polynomials. The proposed two kinds of PA filters, fixed-order and adaptive-order PA filters, are tested on images corrupted by both fixed-valued and random-valued impulsive noise. Major improve- ments are obtained in comparison with other state-of-the-art algorithms. © 1998 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(98)02904-3) Subject terms: image enhancement; image filter; impulse noise; noise detection; noise filtering; polynomial approximation.

Full duplex speakerphone

A full duplex speakerphone for connection to a telephone system employs adaptive FIR filters for acoustic and electrical echo cancellation in a novel combination with analog gain controls responsive to incoming signal levels and a transmit level control responsive to the receive signal power level. The particular combination minimizes the amount of digital signal processing required to maintain full duplex operation by holding the signal dynamic range within predetermined limits.

Developments in cardiovascular ultrasound: Part 1: Signal processing and instrumentation.

One of the major contributions to the improvement of spectral Doppler and colour flow imaging instruments has been the development of advanced signal-processing techniques made possible by increasing computing power. Model-based or parametric spectral estimators, time-frequency transforms, station-arising algorithms and spectral width correction techniques have been investigated as possible improvements on the FFT-based estimators currently used for real-time spectral estimation of Doppler signals. In colour flow imaging some improvement on velocity estimation accuracy has been achieved by the use of new algorithms but at the expense of increased computational complexity compared with the conventional autocorrelation method. Polynomial filters have been demonstrated to have some advantages over IIR filters for stationary echo cancellation. Several methods of velocity vector estimation to overcome the problem of angle dependence have been studied, including 2D feature tracking, two and three beam approaches and the use of spectral width in addition to mean frequency. 3D data acquisition and display and Doppler power imaging have also been investigated. The use of harmonic imaging, using the second harmonic generated by encapsulated bubble contrast media, seems promising particularly for imaging slow flow. Parallel image data acquisition using non-sequential scanning or broad beam transmission, followed by simultaneous reception along a number of beams, has been studied to speed up 'real-time' imaging.

Concurrent vowel identification. III. A neural model of harmonic interference cancellation

This paper presents a “neural cancellation filter” capable of segregating weak targets from competing harmonic backgrounds, and a model of concurrent vowel segregation based upon it. The elementary cancellation filter comprises a delay line and an inhibitory synapse. Filters within each peripheral channel are tuned to the period of the competing sound to suppress its correlates within the neural discharge pattern. In combination with a pattern matching model based on autocorrelation functions summed over channels, the cancellation filter forms a model of concurrent vowel identification. The model predicts the number of vowels reported for each stimulus (when subjects are allowed to report one or two) and identification rates. It belongs to the class of “harmonic cancellation” models that are supported by experimental evidence that vowel identification is better when competing sounds are harmonic than inharmonic. Two alternative schemes using the same filter are also considered. One derives a “place” representation from the magnitude of the filter output. The other uses the ratio of filter input/output to select channels.

Linear and non-linear filters for clutter cancellation in radar systems

The theme of this paper is the cancellation of clutter echoes in modern coherent radar systems. The receiver operating characteristics (ROC) of the following clutter filters are compared: (a) optimum linear filter, (b) the linear filter with Chebyshev tapering, and (c) the non-linear filter which takes the minimum between the outputs of few linear filters which process the same radar signals with properly selected weights. The non-linear filter offers a performance advantage, with respect to the widely used filter (b), in terms of detection capability of a target with Doppler frequency close to the clutter mean Doppler frequency. The non-linear filter requires, in general, five times the computation load of the linear filter (b) but is much less computationally expensive than the optimum linear filter (a).

Beamforming microphone arrays for speech acquisition in noisy environments

In this paper we present an adaptive microphone array with adaptive constraint values to suppress coherent as well as incoherent noise in disturbed speech signals. We use a generalized sidelobe cancelling (GSC) structure implemented in the frequency domain since it allows a separate handling of determining the adaptive look-direction response to suppress incoherent noise and adjusting the adaptive filters for cancellation of coherent noise. The transfer function in the look-direction is an adaptive Wiener-Filter which is estimated by using the short-time Fourier transform and the Nuttall/Carter method for spectrum estimation. The experimental results demonstrate that the proposed method works well for a large range of reverberation times and is therefore able to operate independently of the correlation properties of the noise field.

Feed-forward active filter for output ripple cancellation

An active filter for DC-DC converter ripple cancellation is described and demonstrated. The feed-forward technique used applies to any converter with an output filter inductor. The technique is inherently stable, performs in both continuous and discontinuous conduction modes, and applies to both square-wave and resonant converters. A suitable linear amplifier, combined with a current transformer, implements it with low loss. An adaptive tuning scheme compensates for inductance variation and drift. Operation is demonstrated with buck, push-pull, and boost converter topologies. The result is output ripple below 10 mV RMS, effective on converters with outputs as low as 2 V and currents above 30 A.

New nonlinear adaptive FIR digital filter for broadband noise cancellation

The structure and the adaptive algorithm of a new nonlinear adaptive FIR digital filter. Called nonlinear delayed N-path adaptive FIR (NDNAFIR) digital filter, is presented for cancelling broadband noise from signals containing sharp edges. The filter structure is obtained by decomposing a FIR digital filter into N delayed parallel subfilters which facilitates high speed implementation. Adjustable bipolar sigmoid functions are placed at the output of each subfilter as well as after the summation of all subfilter outputs. Simulation results show that the ND-NAFIR digital filter outperforms those of the linear adaptive FIR digital filter and the nonlinear median filter in broadband noise cancellation in terms of convergence speed and average squared difference between original and recovered signals. >

Adaptive IIR comb filter for harmonic signal cancellation

A novel adaptive infinite impulse response (IIR) comb filter structure for the estimation and elimination of harmonic interference signals is presented. Two filter blocks are presented. The first is an adaptive notch filter implemented by a computationally simple but exact gradient-based algorithm. The adaptive notch filter is used to estimate and track the fundamental frequency of the harmonic series. The second block is a tunable IIR comb filter whose parameters are determined based on the estimate of the fundamental frequency. The purpose of both filter blocks is to effectively cancel the harmonic series. The proposed comb filtering is more robust as well as computationally simpler than the comb filtering technique used by Nehorai and Poraz (1986). Error surface analysis is included to indicate that the error surface characteristics for the proposed solution is a significant improvement when compared to the conventional adaptive comb filter approach used by Nehorai and Poraz (1986). Simulation results are included to demonstrate the performance characteristics of the proposed solution.

A tree-structured piecewise linear adaptive filter

The authors propose and analyze a novel architecture for nonlinear adaptive filters. These nonlinear filters are piecewise linear filters obtained by arranging linear filters and thresholds in a tree structure. A training algorithm is used to adaptively update the filter coefficients and thresholds at the nodes of the tree, and to prune the tree. The resulting tree-structured piecewise linear adaptive filter inherits the robust estimation and fast adaptation of linear adaptive filters, along with the approximation and model-fitting properties of tree-structured regression models. A rigorous analysis of the training algorithm for the tree-structured filter is performed. Some techniques are developed for analyzing hierarchically organized stochastic gradient algorithms with fixed gains and nonstationary dependent data. Simulation results show the significant advantages of the tree-structured piecewise linear filter over linear and polynomial filters for adaptive echo cancellation. >

Partial spectrum reconstruction using digital filter banks

The problem of reconstructing a part of the spectrum is reduced to designing the filter bank to satisfy a set of conditions. For the case considered here, these conditions cannot be satisfied simultaneously, so perfect reconstruction is not possible. The necessary and sufficient conditions on the filters so that the resulting filter bank cancels most alias components are found. Such filter banks are called partial alias cancellation filter banks. The product of the polyphase transfer matrices of these filter banks must be a block pseudocirculant matrix. An algorithm design procedure is discussed, and examples are given to demonstrate the theory.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Performance monitoring in non-linear adaptive noise cancellation

Correlation-based model validity tests are introduced to monitor the operation of non-linear adaptive noise cancellation filters and to detect whether the filters are operating correctly or incorrectly. The tests are derived for a NARMAX (Non-linear Autor-Regressive Moving Average model with eXogenous inputs) filter design based on a Sub-Optimal Least Squares (SOLS) estimation algorithm. Simulation studies are included to illustrate the performance of the new tests.