Introduction of fuzzy logic in the hidden markov models
نویسندگان
چکیده
In this paper, we present a fuzzy logic integration to the Hidden Markov Models (HMM). We have replaced the basic arithmetic operators by some adequate k z y operators. Using fuzzy operators permits us to relax the additivity constraint of probability measures. So we will need only the monotonicity with respect to set inclusion. Some results show the interest of our approach.
منابع مشابه
MAN-MACHINE INTERACTION SYSTEM FOR SUBJECT INDEPENDENT SIGN LANGUAGE RECOGNITION USING FUZZY HIDDEN MARKOV MODEL
Sign language recognition has spawned more and more interest in human–computer interaction society. The major challenge that SLR recognition faces now is developing methods that will scale well with increasing vocabulary size with a limited set of training data for the signer independent application. The automatic SLR based on hidden Markov models (HMMs) is very sensitive to gesture's shape inf...
متن کاملIntroducing Busy Customer Portfolio Using Hidden Markov Model
Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...
متن کاملReliability Assessment of Power Generation Systems in Presence of Wind Farms Using Fuzzy Logic Method
A wind farm is a collection of wind turbines built in an area to provide electricity. Wind power is a renewable energy resource and an alternative to non-renewable fossil fuels. In this paper impact of wind farms in power system reliability is investigate and a new procedure for reliability assessment of wind farms in HL1 level is proposed. In proposed procedure, application of Fuzzy – Markov f...
متن کاملGeneralized hidden Markov models. II. Application to handwritten word recognition
This is the second paper in a series of two papers describing a novel approach for generalizing classical hidden Markov models using fuzzy measures and fuzzy integrals and their application to the problem of handwritten word recognition. This paper presents an application of the generalized hidden Markov models to handwritten word recognition. The system represents a word image as an ordered li...
متن کاملA Comparative Study of the Protein Secondary Structure Prediction methods
Computationally biology is the innovative research for better drug designing. A number of classifiers and techniques are used for prediction of secondary structure prediction of proteins. The basic aim of this paper shows the comparative study by using these three models: Artificial Neural Network, Fuzzy Logic, and Hidden Markov Model and to acquire the optimum end result.
متن کامل