DocumentCode
2637666
Title
Numerical modeling of continuous-time fully coupled neural networks
Author
Zurada, Jacek M. ; Kang, M.J.
Author_Institution
Dept. of Electr. Eng., Louisville Univ., KY, USA
fYear
1991
fDate
18-21 Nov 1991
Firstpage
1924
Abstract
Numerical performance modeling of fully coupled continuous-time networks utilizing continuous activation functions, finite input resistance of neurons, and other parasitic components within the neural systems is discussed. Both time-domain performance modeling and static numerical modeling of the networks are characterized and compared. The main focus is the dynamic and static numerical modeling of actual Hopfield-type networks
Keywords
approximation theory; neural nets; relaxation theory; time-domain analysis; Hopfield-type networks; continuous activation functions; continuous-time fully coupled neural networks; dynamic numerical modelling; finite input resistance; numerical performance modelling; parasitic components; static numerical modeling; time-domain performance modeling; Capacitance; Convergence; Electric resistance; Equations; Neural networks; Neurofeedback; Neurons; Numerical models; Time domain analysis; Voltage;
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.1991.170655
Filename
170655
Link To Document