Abstract:
Recurrent Neural Networks and linear Recursive Filters can be adapted on-line but sometimes with instability problems. Stability control techniques exist for the linear c...Show MoreMetadata
Abstract:
Recurrent Neural Networks and linear Recursive Filters can be adapted on-line but sometimes with instability problems. Stability control techniques exist for the linear case but they are either computationally expensive or non-robust. For the nonlinear case, stability control is simply never done. This paper presents a new stability control method for ITR adaptive filters that makes possible to continually adapt the coefficients with no need of stability test or poles projection. This method can be applied to various realizations: direct forms, cascade or parallel of second order sections, lattice form. It can be implemented to adapt a simple ER adaptive filter or a locally recurrent neural network such as the LR-MLP with improved performance over other techniques and over not controlling the stability.
Published in: 9th European Signal Processing Conference (EUSIPCO 1998)
Date of Conference: 08-11 September 1998
Date Added to IEEE Xplore: 23 April 2015
Print ISBN:978-960-7620-06-4
Conference Location: Rhodes, Greece