| Paper: | SPTM-P12.6 | ||
| Session: | Adaptive Systems and Filtering I | ||
| Time: | Friday, May 19, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Adaptive Systems and Filtering | ||
| Title: | Computationally Efficient Norm-Constrained Adaptive Blind Deconvolution Using Third-Order Moments | ||
| Authors: | Patrik Pääjärvi, James LeBlanc, Luleå University of Technology, Sweden | ||
| Abstract: | Third-order central moments have been shown to be well suited as objective functions for blind deconvolution of impulsive signals. On-line implementations of such algorithms may suffer from increasing filter norm, forcing adaptation under constrained filter norm. This paper extends a previously known efficient algorithm with self-stabilizing properties to the case of using a third-order moment objective function. New results herein use averaging analysis to determine adaptation stepsize conditions for asymptotic stability of filter norm. | ||
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