Chaotic episodic associative memory

In this paper, we propose a chaotic associative memory (CEAM). It can deal with complex episodes which have common terms. The proposed CEAM is based on the conventional temporal associative memory and has connections in the input layer for autoassociation. Each scene of the episodes is memorized together with its own contextual information. The CEAM employs chaotic neurons in a part of the input layer corresponding to contextual information. The chaotic neurons change their states by chaos. As a result, the CEAM can associate plural episodes that have common terms.