Title :
Multilayer neural network structure as Volterra filter
Author :
Osowski, Stanislaw ; Quang, Thanh Vu
Author_Institution :
Inst. of Theory of Electr. Eng. & Elec. Meas., Tech. Univ. Warsaw, Poland
fDate :
30 May-2 Jun 1994
Abstract :
The paper presents the application of the successive linearization to the neural network implementation of the Volterra filter. Applying the signal flow graph approach the new learning rules for adaptation of weights of the obtained multilayer network structure are given. The presented multilayer structure is applied to signal processing including the identification of the parameters of the plant, noise canceling and signal prediction
Keywords :
Volterra series; feedforward neural nets; filtering theory; interference (signal); learning (artificial intelligence); multilayer perceptrons; prediction theory; signal flow graphs; Volterra filter; learning rules; multilayer neural network structure; neural network implementation; noise canceling; signal flow graph approach; signal prediction; signal processing; successive linearization; weight adaptation; Equations; Finite impulse response filter; Flow graphs; Kernel; Multi-layer neural network; Neural networks; Nonhomogeneous media; Nonlinear filters; Signal processing; Signal processing algorithms;
Conference_Titel :
Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on
Conference_Location :
London
Print_ISBN :
0-7803-1915-X
DOI :
10.1109/ISCAS.1994.409564
