An efficient model for systems with complex responses [neural network architecture for nonlinear filtering]

Author

Tresp, Volker ; Leuthäusser, Ira ; Schlang, Martin ; Neuneier, Ralph ; Abraham-Fuchs, Klaus ; Härer, Wolfgang

Author_Institution

Siemens AG, Munchen, Germany

fYear

1992

fDate

31 Aug-2 Sep 1992

Firstpage

493

Lastpage

502

Abstract

Presents a neural network architecture for a restricted class of nonlinear filtering applications. The filter architecture is particularly suited for biomedical and technical applications that require long and complex system responses. The filter architecture was successfully used in a biomedical application for the removal of the cardiac interference from magnetoencephalographic (MEG) data and performed better than standard linear filters and the time-delay neural network

Keywords

adaptive filters; biomagnetism; brain; interference suppression; medical signal processing; neural nets; MEG; biomedical application; cardiac interference removal; complex responses; magnetoencephalographic data; neural network architecture; nonlinear adaptive filters; nonlinear filtering; Biomedical engineering; Filtering; Finite impulse response filter; Interference cancellation; Magnetic separation; Neural networks; Nonlinear equations; Nonlinear filters; Research and development; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing [1992] II., Proceedings of the 1992 IEEE-SP Workshop

Conference_Location

Helsingoer

Print_ISBN

0-7803-0557-4

Type

conf

DOI

10.1109/NNSP.1992.253663

Filename

253663