Design and analysis of associative memories based on external inputs of continuous bidirectional associative networks

This paper presents an extended continuous bidirectional associative memory network (CBAM) and a new ring recurrent network to behave as associative memories with external inputs. The proposed networks are robust in terms of design parameter selection. Some globally exponential stable criteria are derived for the networks with high storage capacity. The approach, by generating networks where the input data are fed via external inputs rather than initial conditions, enables multiple prototype patterns to be retrieved simultaneously. The results improve and extend some previous related works. Recurring to the numerical method, several applicable examples are given to illustrate the effectiveness of the proposed networks.