DocumentCode :
2636876
Title :
Nonlinear neural field filters
Author :
Sherief, H.T. ; Fatmi, H.A.
Author_Institution :
King´´s Coll. London, London Univ., UK
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
1885
Abstract :
Design, stability and implementation of nonlinear neural field filters are examined. The input and output of the neural field filters are vector fields. A neural transform is used to represent the input, output signals and the transfer function of the neural field filter. It is concluded that the Lyapunov conditions for such fields are taken care of by a novel extension of the Routh stability criteria, which uses the neural transform operator along with the Mobius transform
Keywords :
filtering and prediction theory; neural nets; stability criteria; transfer functions; Lyapunov conditions; Mobius transform; Routh stability criteria; neural transform; nonlinear neural field filters; transfer function; Differential equations; Displays; Educational institutions; Nonlinear filters; Partial differential equations; Signal mapping; Stability criteria; Topology; Transfer functions; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170642
Filename :
170642
Link To Document :
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