This tutorial presents an introduction to the studies undertaken by the authors and their collaborators between 1997 and 2009 on the topic of dissimilarity representations for pattern recognition.

Currently, the best performing state-of-art large vocabulary speech recognition systems are statistical pattern classifiers which model sound units using hidden Markov models (HMMs). Given a sequence of data X derived from the speech signal, the classification problem that is solved is that of finding the class c(X) for which the following expression, given by Bayes classification rule, is maxi...

In this paper, the correlation measure of neutrosophic refined(multi-) sets is proposed. The concept of this correlation measure of neutrosophic refined sets is the extension of correlation measure of neutrosophic sets and intuitionistic fuzzy multi-sets. Finally, using the correlation of neutrosophic refined set measure, the application of medical diagnosis and pattern recognition are presented.