Abstract-A new online method to optimize the free parameter in adaptive Laguerre-based filters is presented. It is based on the minimization of a criterion that is equivalent to an upper bound for the quadratic approximation error. The proposed technique presents a fast convergence and a good robustness.

International audienceKautz functions have received much attention in the recent mathematical modeling and identification literature. These functions which involve free parameters can approximate efficiently signals with strong oscillatory behavior. We consider here the choice of the free parameters in discrete (two-parameter) Kautz approximation. Using a key relationship between Kautz and Laguerre expansions we derive an upper bound for the quadratic truncation error. Minimization of this upper bound yields pertinent parameters, whose computation then requires reduced knowledge of the function to be modeled

"©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."International audienceWe report on our investigations to choose a free parameter to minimize the error energy when approximating a given signal with orthogonal basis functions. This method requires limited knowledge of the signal to be approximated and has a low computational cost

A procedure for determining two parameters to be used in Kautz approximation is presented. It is based on minimisation of an upper bound of the error energy.

International audienceA simplified algorithm for the efficient computation of sequences required in the Laguerre transform signal analysis of transients on uniformly distributed RGC lines is derived