180 research outputs found

    A highly modular adaptive lattice algorithm for multichannel least squares filtering

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    In this paper a highly modular adaptive lattice algorithm for multichannel least squares FIR filtering and multivariable system identification is presented. Multichannel filters with different number of delay elements per input channel are allowed. The main features of the proposed multichannel adaptive lattice least squares algorithm is the use of scalar only operations, multiplications/divisions and additions, and the local communication which enables the development of a fully pipelining architecture. The tracking capability and the numerical stability and accuracy of the proposed technique are illustrated by simulations

    The generalized sliding window recursive least-squares (SGW RLS) algorithm

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    RLS Adaptive Filtering Algorithms Based on Parallel Computations

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    The paper presents a family of the sliding window RLS adaptive filtering algorithms with the regularization of adaptive filter correlation matrix. The algorithms are developed in forms, fitted to the implementation by means of parallel computations. The family includes RLS and fast RLS algorithms based on generalized matrix inversion lemma, fast RLS algorithms based on square root free inverse QR decomposition and linearly constrained RLS algorithms. The considered algorithms are mathematically identical to the appropriate algorithms with sequential computations. The computation procedures of the developed algorithms are presented. The results of the algorithm simulation are presented as well

    The Fast Affine Projection Algorithm

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    This paper discusses a new adaptive filtering algorithm called fast affine projections (FAP). FAP\u27\u27s key features include LMS like complexity and memory requirements (low), and RLS like convergence (fast) for the important case where the excitation signal is speech. Another of FAP\u27\u27s important features is that it causes no delay in the input or output signals. In addition, the algorithm is easily regularized resulting in robust performance even for highly colored excitation signals. The combination of these features make FAP an excellent candidate for the adaptive filter in the acoustic echo cancellation problem. A simple, low complexity numerical stabilization method for the algorithm is also introduced
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