Abstract:
The Wiener series is one of the standard methods to systematically characterize the nonlinearity of a system. The classical estimation method of the expansion coefficient...Show MoreMetadata
Abstract:
The Wiener series is one of the standard methods to systematically characterize the nonlinearity of a system. The classical estimation method of the expansion coefficients via cross-correlation suffers from severe problems that prevents its application to high-dimensional and strongly nonlinear systems. We propose an implicit estimation method based on regression in a reproducing kernel Hubert space that alleviates these problems. Experiments show performance advantages in terms of convergence, interpretability, and system sizes that can be handled
Published in: Proceedings of the 2004 14th IEEE Signal Processing Society Workshop Machine Learning for Signal Processing, 2004.
Date of Conference: 29 September 2004 - 01 October 2004
Date Added to IEEE Xplore: 02 May 2005
Print ISBN:0-7803-8608-4
Print ISSN: 1551-2541