Generally the fractal image compression is a technique based on the presentation of an image by a contractive transform, on the space of image, for which the fixed point is close to the original image. The fractal image compression is rapidly growing principle covers a wide variety of coding scheme in various domains. A large number of theoretical aspects of this concept are available. However,...

The standard model fermion spectrum, including a right handed neutrino, can be obtained as a zero-mode of the Dirac operator on a space which is the product of complex projective spaces of complex dimension two and three. The construction requires the introduction of topologically non-trivial background gauge fields. By borrowing from ideas in Connes’ non-commutative geometry and making the com...

A new decision support system is developed for assisting business executives in deciding the e-business models to adopt for new business ventures. The developed system is based on a new framework using fuzzy logic theory. A detailed conceptual design is developed. The proposed system solves important challenges such as the use of linguistic terms to capture the executives’ assessments of the ke...

An adaptive fuzzy inference neural network (AFINN) is proposed in this paper. It has self-construction ability, parameter estimation ability and rule extraction ability. The structure of AFINN is formed by the following four phases: (1) initial rule creation, (2) selection of important input elements, (3) identification of the network structure and (4) parameter estimation using LMS (least-mean...

Computing with words applications are mostly built using rule-based systems, which have some important deficits: First, it is not easy to deal with high dimension problems because the size of the rule base increases exponentially; second, it is not possible to concatenate two or more systems without losing information; and third, there are no ways to compute inputs from outputs. In this article...

In the early 1970s, fuzzy systems and fuzzy control theories added a new dimension to control systems engineering. From its beginnings as mostly heuristic and somewhat ad hoc, more recent and rigorous approaches to fuzzy control theory have helped make it an integral part of modern control theory an... Reflecting the tremendous advances that have taken place in the study of fuzzy set theory and...

Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text classification. In this paper, Fast Fuzzy Feature clustering for text classification is proposed. It is based on the framework proposed by Jung-Yi Jiang, Ren-Jia Liou and Shie-Jue Lee in 2011. The word in the feature vector of the document is grouped into the cluster in less iteration. The numbers o...

We introduce a new clustering method for DNA microarray data that is based on space filling curves and wavelet denoising. The proposed method is much faster than the established fuzzy c-means clustering because clustering occurs in one dimension and it clusters cells that contain data, instead of data themselves. Moreover, preliminary evaluation results on data sets from Small Round Blue-Cell t...

Satellite image classification is a significant technique used in remote sensing for the computerized study and pattern recognition of satellite information, which make possible the routine explanation of a huge quantity of information. Nowadays cellular automata are implemented for simulation of satellite images and also cellular automata relates to categorization in satellite image is used si...

|To design a fuzzy rule-based classi cation system (fuzzy classi er) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high (or e...