A max-min criterion for design of bidirectional associative memory

which requires the smallest domain of attraction to be maximized

is proposed in this paper. A quick learning algorithm is first given

by which the designed connection weights are 1

0 or -1. Further

a constrained perceptron optimization algorithm is presented

which takes the weights obtained by quick algorithm as initial iteration value. Computer experimental results confirm the advantages of the proposed algorithms.