A Pattern Classifier Integrating Multilayer Perceptron and Error-Correcting Code

In this paper we present a novel classifier which integrates a multilayer perceptron and a error-correcting decoder. There are two stages in the classifier, in the first stage, mapping feature vectors from feature space to code space is achieved by a multilayer perceptron; in the second stage, error correcting decoding is done on code space, by which the index of the noisy codeword can be obtained. Hence we can get classifications of original feature vectors. The classifier has better classification performances than the conventional multilayer perceptrons.