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