Abstract
The problem of adapting linear and nonlinear recursive filters through a gradient-based optimization procedure is considered. The rigorous application of this technique implies a time-growing computation load. Recently, a method for estimating the weight updates was introduced, leading to a new class of algorithms. The convergence properties of these algorithms, when applied to a linear and then a nonlinear recursive filter, are exhibited through a dynamical analysis of the adaptation process. Since the general analysis is very difficult, the case of a first-order filter with a constant input is considered. Significant results are obtained in this particular application.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.