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QR-Decomposition-Based RLS Filters

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Adaptive Filtering

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Abstract

The application of QR decomposition [1] to triangularize the input data matrix results in an alternative method for the implementation of the recursive least-squares (RLS) method previously discussed. The main advantages brought about by the recursive least-squares algorithm based on QR decomposition are its possible implementation in systolic arrays [2,3,4] and its improved numerical behavior when quantization effects are taken into account [5].

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Notes

  1. 1.

    The reader should note that here the definition of forward prediction error is slightly different from that used in Chaps. 7 and 8, where in the present case we are using the input and desired signals one step ahead. This allows us to use the same information matrix as the conventional QR-Decomposition algorithm of Sect. 9.2.3.

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  1. Universidade Federal do Rio de Janeiro, Niterói, Rio de Janeiro, Brazil

    Paulo S. R. Diniz

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Correspondence to Paulo S. R. Diniz .

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Diniz, P.S.R. (2020). QR-Decomposition-Based RLS Filters. In: Adaptive Filtering. Springer, Cham. https://doi.org/10.1007/978-3-030-29057-3_9

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  • DOI: https://doi.org/10.1007/978-3-030-29057-3_9

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