Title :
Search time of cyclic patterns in chaotic neural network
Author :
Deguchi, T. ; Ishii, N.
Author_Institution :
Gifu Nat. Coll. of Technol., Japan
Abstract :
The chaotic neural networks that learn patterns by associative memory can recall aperiodic pattern sequences including the learned ones. We report that applying presynaptic inhibition to a chaotic neural network to control the chaotic behavior realized the search of cyclic associative memory by matching features with chaos. Nara et al. (1992) reported the search of cyclic associative memory by changing the connection number of neurons. Using the patterns the same as Nara´s report, the same searches ware carried out in chaotic neural networks. The results shows that search by the chaotic neural network can attain a better success rate, but the speed is lower. To improve the time for search the presynaptic inhibition function is reformed
Keywords :
chaos; content-addressable storage; learning (artificial intelligence); neural nets; search problems; aperiodic pattern sequences; chaos; chaotic neural network; cyclic associative memory; cyclic pattern search time; pattern learning; presynaptic inhibition; Associative memory; Biological system modeling; Chaos; Computer science; Educational institutions; Information processing; Intelligent networks; Neural networks; Neurons; State-space methods;
Conference_Titel :
Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-6400-7
DOI :
10.1109/KES.2000.885841