Linear associative memories with optimal rejection to colored input noise

It is known that many linear associative memories are sensitive to input noise. To reduce such noise sensitivity, an approach of designing an optimal-noise-rejection linear associative matrix is presented in this paper. An optimally biased, as well as unbiased solution, in the sense of least-mean-square of recall error for colored input noise, is given. The theoretical lower bound of error for biased or unbiased recall is derived. A recursive computational procedure for the optimal design is proposed. Computer simulation and image recall experiments illustrate a superior noise rejection of the proposed approach.