Handling uncertainty and vagueness in real world becomes a necessity for developing intelligent and efficient systems. Based on the credibility theory, a fuzzy clustering approach that improves the classification accuracy is targeted by this work. This paper introduces a design of an efficient set of fuzzy rules that are inferred by a hybrid model of SOFM (Self Organized Features Maps) and FRAN...

Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of this theory to gray level images. One of these techniques is based on fuzzy logic and on the theory...

Complex fuzzy systems exist in many applications and effective visualisation is required to gain insights into the nature and working of these systems, especially in the implication of imprecision, its propagation and impacts on the quality and reliability of the outcomes. This paper presents a holistic approach towards the design of a visualisation system for fuzzy systems. We firstly analyse ...

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...

In this paper, we talk about the application of fuzzy control techniques to the nonlinear systems. We propose a new scheme of fuzzy optimal control techniques in which T-S (Takagi-Sugeno) fuzzy model is used for the modeling. We adopt the PDC (parallel distributed control) as our controller which is also modeled by fuzzy rules. Both the discrete system case and the continuous system case are di...

Data mining techniques can be used to discover useful patterns by exploring and analyzing data, so, it is feasible to incorporate data mining techniques into the classification process to discover useful patterns or classification rules from training samples. This paper thus proposes a data mining technique to discover fuzzy classification rules based on the well-known Apriori algorithm. Signif...

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing t...

A robust thresholding technique is proposed in this paper for segmentation of brain MR images. It is based on the fuzzy thresholding techniques. Its aim is to threshold the gray level histogram of brain MR images by splitting the image histogram into multiple crisp subsets. The histogram of the given image is thresholded according to the similarity between gray levels. The similarity is assesse...

Defuzzification converts the final fuzzy output set of fuzzy controller and fuzzy inference systems to a significant crisp value. However, there are various mathematical methods for defuzzification, but there is not any certain systematic method for choosing the best strategy. In this paper, first we explain the structure of a fuzzy inference system and then after a short review of defuzzificat...

With the explosive growth of data available on the Internet, a recent area of investigation called Web Mining has arise. In this paper, we will study general aspects of this area, principally the process of Web Usage Mining where log files are analyzed. These files register the activity of the user when interact with the Web. In the Web Usage Mining, different techniques of mining to discover u...