Title :
Exponential stability of delayed bi-directional associative memory networks
Author_Institution :
Dept. of Appl. Math., Southeast Univ., Nanjing, China
Abstract :
Some sufficient conditions are derived for the global exponential stability in delayed bi-directional associative memory (BAM) networks by constructing a suitable Lyapunov functional and the inequality 2ab⩽a 2+b2 technique. These conditions have an important leading significance in the design and applications of globally exponentially stable neural circuits for delayed BAM
Keywords :
Lyapunov methods; asymptotic stability; content-addressable storage; functional equations; neural nets; Lyapunov functional; delayed bi-directional associative memory networks; exponential stability; globally exponentially stable neural circuits; sufficient conditions; Artificial neural networks; Associative memory; Bidirectional control; Circuit stability; Delay effects; Hydrogen; Magnesium compounds; Mathematics; Neural networks; Sufficient conditions;
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
DOI :
10.1109/ICOSP.2000.893435
