Fundamentals of Adaptive Signal Processing by Aurelio Uncini

Author:Aurelio Uncini
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

(6.186)

where, in the case of stochastic gradient, and are the estimates gradient and the inverse Hessian of the CF. So, by extending the model (6.186), we can identify new paradigms of adaptation.

A first adaptation law, more general than (6.186), is a rule in which the weights w k linearly depend on the weights of the instantly (k − 1). In formal terms, we can write

(6.187)

where M k and are independent of w k . For example, in (6.186) and M k  = I. A second, even more general, model consists in the definition of a nonlinear relationship of the type

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