Abstract
Fast QR decomposition (QRD) RLS algorithms based on backward prediction errors are well known for their good numerical behavior and their low complexity when compared to similar algorithms with forward error update. Although the basic matrix expressions are similar, their application to multiple channel input signals generate more complex equations. This paper presents a lattice version of the multichannel fast QRD algorithm based on a posteriori backward errors updating. This new algorithm comprises scalar operations only; its modularity and pipelinability favors its systolic array implementation.KeywordsPrediction ErrorCholesky FactorSpeech EnhancementOrder MatrixScalar OperationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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