Lucent Technologies Inc.

Agere Systems Inc.

At+t Corp.

Steven Leslie Gay

Jacob Benesty

Man Mohan Sondhi

Tomas Fritz Gaensler

A robust adaptive filter for use in a network echo canceller or other digital signal processing application utilizes a coefficient vector update device that, through the application of fast converging algorithms to a fast impulse response filter yields fast convergence of the adaptive filter's characteristics with the avoidance of divergence due to the onset of double talk. Robustness is also provided, via an adaptive scale non-linearity device which applies an adaptive scale non-linearity to the filter algorithms fed to the fast impulse response filter by the coefficient vector update device, so that the samples of an echo signal to be cancelled which are taken during the onset of double talk can be handled in such a manner that after the double talk detector causes adaptation to cease, the initial, potentially disturbing samples do not cause significant divergence in the filter system.

Adaptive filter for network echo cancellation

The present invention provides an adaptive filter. In one embodiment, the adaptive filter includes a solution vector generator that develops a sparse expression of an initial solution vector. In addition, the adaptive filter includes a proportionate normalized least mean squares (PNLMS) analyzer, coupled to the solution vector generator, that employs the sparse expression to converge upon at least one coefficient for the adaptive filter.

Solution space principle component-based adaptive filter and method of operation thereof

A method is presented for dynamic resource allocation in a speech signal echo canceler enabling more efficient echo cancellation and as a result the ability for an Integrated Circuit to handle additional channels than heretofore possible. This is accomplished by applying one or more of three efficiency enhancing strategies. First, no update of coefficients is computed or convolution performed if the power level of the far end speech signal is below a given threshold. Second, convolution is limited to the set of active taps (i.e., taps that account for most of the power in the echo). Third, new coefficients are computed only when the power of the error signal is greater than a given threshold. Lastly, the set of active coefficients is periodically updated. These strategies release computational resources from unnecessary computations and divert them to other channels that may be active.

Dynamic allocation of resources for echo cancellation

An adaptive filter suitable for network echo cancellation and other applications contains a coefficient vector update device for feeding coefficient vector updates to a finite impulse response filter in accordance with fast converging algorithms. A double talk detector is included for causing filter adaptation to cease in the presence of double talk in the system being echo cancelled. The coefficient vector update device utilizes a proportional affine projection algorithm to provide fast convergence of the filter system and improved performance over other filter devices utilizing different fast converging algorithms.

Adaptive filter utilizing proportional affine projection algorithm

Method and apparatus for network echo cancellation using a proportionate normalized least mean squares algorithm

A dynamically regularized fast recursive least squares (DR-FRLS) adaptive filter and method are disclosed which provide O(N) computational complexity and which have dynamically adjusted regularization in real-time without requiring restarting the adaptive filtering. The adaptive filter includes a memory for storing at least one program, including a dynamically regularized fast recursive least squares (DR-FRLS) program; and a processor which responds to the DR-FRLS program for adaptively filtering an input signal and for generating an output signal associated with the input signal.

Adaptive filter and method for implementing echo cancellation

A fast affine projection adaptive filter capable of frequent parameter updating and fast convergence with low complexity. The invention mitigates affine projection adaptive filter complexity due to matrix inversion and the fact that a given excitation vector is weighted and summed into the adaptive coefficient vector many times. Embodiments of the invention achieve fast convergence through sample by sample updating and the exploitation of the shift invariant property of the excitation signal. Complexity is further reduced by a vector update procedure in which a given excitation vector is weighted and added into the coefficient estimate only once. Three illustrative embodiments are presented. The first of these is a relaxed adaptive filter, the second is an adaptive filter without relaxation and a third is an adaptive filter with suspended adaptation. The embodiments are presented in the context of electrical and acoustic echo cancellation.

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Long Valley, NJ, United States of America

Steven Leslie Gay