Chaos control and associative memory of a time-delay globally coupled neural network using symmetric map

A chaotic neural network called time-delay globally coupled neural network using symmetric map (TDSG) is proposed for information processing applications. Firstly, its rich dynamic behaviors are exhibited and the output stability is demonstrated by using a parameter modulated control method. Secondly, the associative memory of TDSG is investigated by the control method. It is observed that the stable output sequence only contains stored pattern and its reverse pattern and the TDSG finally converges to the stored pattern which has the smallest Hamming distance to the initial patterns with noise. At last, strong information recovery ability of the TDSG is illustrated by comparative experiments.