Title :
On the domain of attraction and convergence rate of Hopfield continuous feedback neural networks
Author_Institution :
Dept. of Appl. Math., Southeast Univ., Nanjing, China
Abstract :
The domain of attraction of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are estimated by means of a matrix measure and a comparison principle. These results can be used for the evaluation of fault-tolerance capability and the synthesis procedures for Hopfield continuous feedback associative memory neural networks
Keywords :
Hopfield neural nets; content-addressable storage; convergence; fault tolerant computing; feedback; Hopfield continuous associative memory; Hopfield continuous feedback neural networks; comparison principle; domain of attraction; exponential convergence rate; fault-tolerance capability; matrix measure; memory patterns; network trajectories; synthesis procedures; Associative memory; Convergence; Differential equations; Fault tolerance; Hopfield neural networks; Mathematics; Network synthesis; Neural networks; Neurofeedback; State feedback;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863131
