Abstract
Further developing the idea of a cascade structure for adaptive linear prediction with independently adapting low-order stages, we develop a new implementation where the single stages use the forward-backward linear prediction algorithm. Combining the advantages of the cascade structure, which is less affected by the eigenvalue spread and mode coupling, with the reduced misadjustment of the forward-backward predictor delivers a new structure with improved performance. This new structure is capable of faster and more accurate tracking of nonstationary inputs in the early stage of the adaptation.
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