Method of the estimation of the parameters of a variable length Markov chain based on Fisher’s exact test

A method of the estimation of the parameters of a variable length Markov chain based on the use of Fisher’s exact test is proposed. The method has been applied to the problem of classification of convolutionally coded binary signals. Computer simulation has shown that the constructed models have a considerably smaller number of parameters as compared to the models based on the Kullbak-Leibler criterion, which is very popular in constructing variable-order Markov models.