ON GENERALIZED ADAPTIVE NEURAL FILTERS
Document Type
Conference Proceeding
Publication Date
1-1-1992
Abstract
The generalized adaptive neural filter(GANF), a new class of nonlinear filters, is introduced. It is effective for non-Gaussian noise suppression. In this paper, some properties of GANF are derived, and an algorithm for finding the optimal GANF, based on the upper bound in the Minimum Absolute Error(MAE), is proposed. The implementation of the optimal GANF by using the Least Mean Square Error(LMS) and the Least Perceptron Error(LP) is also discussed. Experimental results are presented to demonstrate the effectiveness of the new filter.
Identifier
85024224136 (Scopus)
ISBN
[0780305590]
Publication Title
Proceedings of the International Joint Conference on Neural Networks
External Full Text Location
https://doi.org/10.1109/IJCNN.1992.227329
First Page
277
Last Page
282
Volume
4
Recommended Citation
Zhang, Zeeman Z.; Ansari, Nirwan; and Lin, Jean Hsang, "ON GENERALIZED ADAPTIVE NEURAL FILTERS" (1992). Faculty Publications. 17460.
https://digitalcommons.njit.edu/fac_pubs/17460
