Search time of cyclic patterns in chaotic neural network
Toshinori Deguchi, Naohiro Ishii · 2002
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.