In this paper the theory of fuzzy logic is mixed with the theory of Markov systems and the abstraction of a Markov system with fuzzy states introduced. The notions such as fuzzy transient, fuzzy recurrent etc., were introduced. The results based on these notions are introduced.

A computationally simple approach of model order reduction for single input single output (SISO) and linear timeinvariant discrete systems modeled in frequency domain is proposed in this paper. Denominator of the reduced order model is determined using fuzzy C-means clustering while the numerator parameters are found by matching time moments and Markov parameters of high order system. Keywords—...

A generalised fuzzy approach to statistical modelling techniques for speech recognition is proposed in this paper. Fuzzy C-means (FCM) and fuzzy entropy (FE) techniques are combined into a generalised fuzzy technique and applied to hidden Markov models (HMMs). A more robust version of the above fuzzy technique based on the noise clustering (NC) method is also proposed. Experimental results were...

Our work consists in implementing a new two-dimensional descriptor in Text Mining. After the morphosyntaxic analysis of the words using the techniques of automatic treatment of the natural language, there is lost additional information which we will not neglect but rather put in a new dimension. This involves a rewriting of weight descriptors in documents by a new "fuzzy" measure. The applicati...

Although data mining is relative young technique, it has been used in a wide range of problem domains over the past few decades. In this paper, the authors present a new model to forecast the cultivated land demand adopts the technique of data mining. The new model which is called fuzzy Markov Chain model with weights ameliorate the traditional Time Homogeneous Finite Markov chain model to pred...

We describe a novel technique to combine motion data with scene information to capture activity characteristics of older adults using a single Microsoft Kinect depth sensor. Specifically, we describe a method to learn activities of daily living (ADLs) and instrumental ADLs (IADLs) in order to study the behavior patterns of older adults to detect health changes. To learn the ADLs, we incorporate...

This paper presents availability computation procedure of a semi-Markovian mechatronic system under the uncertainties that involve randomness as well as fuzziness. Conversion of semi-Markov to Markov model is stated first and hybrid approach is then used for fuzzy availability computation. Sometimes statistical data is available about failure and repair rates, but in cases where such data is sc...

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.

Automatically recognizing the e-learning activities is an important task for improving the online learning process. Probabilistic graphical models such as Hidden Markov Models and Conditional Random Fields have been successfully used in order to identify a web user activity. For such models, the sequences of observation are crucial for training and inference processes. Despite the efficiency of...

In the conventional hidden Markov model, the model parameters are reestimated by an iterative procedure known as the Baum-Welch method. This paper proposes an alternative procedure using fuzzy estimation, which is generalised from the fuzzy c-means and the BaumWelch methods. An extension of this approach, which uses a garbage state to deal with outlier data is also proposed. Experiments using t...