Title :
On the analysis of neural networks with asymmetric connection weights or noninvertible transfer functions
Author :
Liang, Ping ; Xiong, Kaiqi
Author_Institution :
Dept. of Electr. Eng., California Univ., Riverside, CA, USA
fDate :
10/1/1999 12:00:00 AM
Abstract :
This paper extends the energy function to the analysis of the stability of neural networks with asymmetric interconnections and noninvertible transfer functions. Based on the new energy function, stability theorems and convergent criteria are derived which improve the available results in the literature. A simpler proof of a previous result for complete stability is given. Theorems on complete stability of neural networks with noninvertible output functions are presented
Keywords :
neural nets; stability; transfer functions; asymmetric connection weights; convergent criteria; neural networks; noninvertible output functions; noninvertible transfer functions; stability; Cellular neural networks; Differential equations; Hopfield neural networks; Neural networks; Neurons; Recurrent neural networks; Stability analysis; Stability criteria; Symmetric matrices; Transfer functions;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.790447
