Comparative study on the generalized adaptive neural filter with other nonlinear filters

Henry Hanek, Nirwan Ansari, Zeeman Z. Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

The Generalized Adaptive Neural Filter (GANF) is a new type of adaptable filter. The GANF relies upon neural functions to set up a filtering operation. This paper looks at a few of the possible neural operators which can be used in a GANF. The capabilities of the neural nets are examined and the filtering abilities of the GANF are obtained through simulation. While the GANF structure used here is somewhat simplified, the filter is also compared to other non-adaptive filters. These filters provide a reference so that relative performance can be more realistically judged.

Original languageEnglish (US)
Title of host publicationPlenary, Special, Audio, Underwater Acoustics, VLSI, Neural Networks
PublisherPubl by IEEE
ISBN (Print)0780309464
StatePublished - Jan 1 1993
Event1993 IEEE International Conference on Acoustics, Speech and Signal Processing - Minneapolis, MN, USA
Duration: Apr 27 1993Apr 30 1993

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume1
ISSN (Print)0736-7791

Other

Other1993 IEEE International Conference on Acoustics, Speech and Signal Processing
CityMinneapolis, MN, USA
Period4/27/934/30/93

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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