Fuzzy clustering algorithms like the popular fuzzy cmeans algorithm (FCM) are frequently used to automatically divide up the data space into fuzzy granules (fuzzy vector quantization). In the context of fuzzy systems, in order to be intuitive and meaningful to the user, the fuzzy membership functions of the used linguistic terms have to fulfill some requirements like boundedness of support or u...

Conventional Association Rule Mining (ARM) algorithms usually deal with datasets with categorical values and expect any numerical values to be converted to categorical ones using ranges (Age = 25 to 60). Fuzzy logic is used to convert quantitative values of attributes to categorical ones so as to eliminate any loss of information arising due to sharp partitioning (using ranges) and then generat...

ntil recently, it was possible to distinguish between software-1 and hardware-oriented approaches to design. 2,3 In software-oriented design, the designer implements the system in software and moves modules that do not meet certain requirements to hardware. Hardware-oriented design starts with a fully hardware implementation; the designer moves blocks to software according to delay times. Both,...

Data clustering is an unsupervised data analysis and data mining technique, which offers refined and more abstract views to the inherent structure of a data set by partitioning it into a number of disjoint or overlapping (fuzzy) groups. Hundreds of clustering algorithms have been developed by researchers from a number of different scientific disciplines. The intention of this report is to prese...

Data-based identification of fuzzy rule-based classifiers for high-dimensional problems is addressed. A crisp binary decision tree approach is proposed for the selection of the relevant features and effective initial partitioning of the input domain. The decision tree is then transformed into a fuzzy rule-based classifier. Fuzzy classifiers have more flexible decision boundaries than decision t...

Color is one of the most important image features used in content-based image retrieval (CBIR). This paper proposes a robust and effective color feature known as ring-based fuzzy histogram (RFH), which reduces noise sensitivity in conventional color histograms (CCH) by using two stages of fuzzy clustering. By partitioning images into rings, RFH can capture an image’s spatial information, and is...

A delay partitioning approach is introduced to solve problems of passivity and passification for continuous T-S fuzzy system with time delay. Our aim is to design a state feedback controller such that the resulting closed system is passive. By constructing a Lyapunov-Krasovskii functional, delay-dependent passivity/passification performance conditions are formulated in terms of linear matrix in...

This paper presents a novel technique for improved voting by adaptively varying the membership boundaries of a fuzzy voter to achieve realistic consensus among inputs of redundant modules of a fault tolerant system. We demonstrate that suggested dynamic membership partitioning minimizes the number of occurrences of incorrect outputs of a voter as compared to the fixed membership partitioning vo...

With the capability of dealing with vague and incomplete data, the study of fuzzy time series has attracted great interest and is expected to expand rapidly. Song and Chissom (1993) first proposed the seven-step forecasting framework of fuzzy time series which are composed of (1) definition of the universe of discourse, (2) partitioning of the universe of discourse, (3) definition of fuzzy sets...

Sophisticated fuzzy rule systems are supposed to be flexible, complete, consistent and compact (FC). Flexibility, completeness and consistency are essential for fuzzy systems to exhibit an excellent performance and to have a clear physical meaning, while compactness is crucial when the number of the input variables increases. However, the completeness and consistency conditions are often violat...