Abstract

Many problems in adaptive filtering can be approached from the point of view of system identification. The recursive maximum likelihood algorithm is proposed for estimating the parameters of the signal model. The parameter estimates are then used to form an adaptive infinite impulse response filter. Several examples are discussed including: adaptive line enhancement, adaptive deconvolution, adaptive noise cancelling, and adaptive time delay estimation.

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