Dynamic programming and diagnostic classification

In this paper, the sequential determination of the Moore–Penrose generalized inverse matrix by dynamic programming is applied to the diagnostic classification of electromyography signals. The obtained results are comparable to those in the literature. Moreover, this recursive scheme has the advantage of allowing the inclusion of new diagnostic results in the learning process, as more and more patients are included in the training of the associative memory.