Local and global passivity relations for Gauss-Newton methods in adaptive filtering

Markus Rupp; Ali H. Sayed

doi:10.1117/12.211399

7 June 1995 Local and global passivity relations for Gauss-Newton methods in adaptive filtering

Markus Rupp, Ali H. Sayed

Proceedings Volume 2563, Advanced Signal Processing Algorithms; (1995) https://doi.org/10.1117/12.211399
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

We provide a time-domain analysis of the robustness and stability performance of Gauss- Newton recursive methods that are often used in identification and control. Several free parameters are included in the filter description while combining the covariance update with the weight-vector update; the exponentially weighted recursive least squares algorithm being an important special case. One of the contributions of this work is to show that by properly selecting the free parameters, the resulting filter can be shown to impose certain bounds on the error quantities, thus resulting in desireable robustness and stability properties. We also show that an intrinsic feedback structure, mapping the noise sequence and the initial weight guess to the a priori estimation errors and the final weight estimate, can be associated with such schemes. The feedback configuration is motivated via energy arguments and is shown to consist of two major blocks: a time-variant lossless (i.e., energy preserving) feedforward path and a time-variant feedback path.

Citation Download Citation

Markus Rupp and Ali H. Sayed "Local and global passivity relations for Gauss-Newton methods in adaptive filtering", Proc. SPIE 2563, Advanced Signal Processing Algorithms, (7 June 1995); https://doi.org/10.1117/12.211399

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