s In respect of the de finition of intuitionistic fuzzy n-norm [9] , the definition of generalised intuitionistic fuzzy ψ norm ( in short GIFψN ) is introduced over a linear space and there after a few results on generalized intuitionistic fuzzy ψ normed linear space and finite dimensional generalized intuitionistic fuzzy ψ normed linear space have been developed. Lastly, we have introduced the...

A new learning method, the fuzzy kernel perceptron (FKP), in which the fuzzy perceptron (FP) and the Mercer kernels are incorporated, is proposed in this paper. The proposed method first maps the input data into a high-dimensional feature space using some implicit mapping functions. Then, the FP is adopted to find a linear separating hyperplane in the high-dimensional feature space. Compared wi...

Operations between two granules and inclusion measure are two important issues in granular computing. Two operations between two granules, named join operation and meet operation, are formed to realize the transformation between granule spaces with different granularities, and the fuzzy inclusion measure is induced by the aforementioned operations. The granule set, operations, and fuzzy inclusi...

In this chapter, a new family of multifactorial function, called generalized additive weighted multifactorial function, is proposed and discussed in detail. First, its properties in n-dimensional space are discussed and then our results are extended to the infinite dimensional space. Second, the implication of its constant coefficients is explained by fuzzy integral. Finally, its application in...

This paper is concerned with the application of a treebased regression model to extract fuzzy rules from highdimensional data. We introduce a locally weighted scheme to the identification of Takagi-Sugeno type rules. It is proposed to apply the sequential least-squares method to estimate the linear model. A hierarchical clustering takes place in the product space of systems inputs and outputs a...

The aim of this paper is to characterize $3$-dimensional $N(k)$-paracontact metric manifolds satisfying certain curvature conditions. We prove that a $3$-dimensional $N(k)$-paracontact metric manifold $M$ admits a Ricci soliton whose potential vector field is the Reeb vector field $xi$ if and only if the manifold is a paraSasaki-Einstein manifold. Several consequences of this result are discuss...

Here, a new fuzzy direct torque control algorithm for induction motors is proposed. As in the classical direct torque control, the inverter gate control signals directly come from the optimum switching voltage vector look-up table, the best voltage space vector selection is a key factor to obtain minimum torque and flux ripples. In the proposed approach, the best voltage space vector is sel...

In digital image classification the conventional statistical approaches for image classification use only the gray values. Different advanced techniques in image classification like Artificial Neural Networks (ANN), Support Vector Machines (SVM), Fuzzy measures, Genetic Algorithms (GA), Fuzzy support Vector Machines (FSVM) and Genetic Algorithms with Neural Networks are being developed for imag...

In this note, we aim to present some properties of the space of all weakly fuzzy bounded linear operators, with the Bag and Samanta’s operator norm on Felbin’s-type fuzzy normed spaces. In particular, the completeness of this space is studied. By some counterexamples, it is shown that the inverse mapping theorem and the Banach-Steinhaus’s theorem, are not valid for this fuzzy setting. Also...

2. Abstract space-time. We need first an axiomatic foundation strong enough to support both our mathematical considerations and their applications to physics. DEFINITION. An n+1 dimensional space-time (n*tl) consists of (A) An n+1 dimensional vector space V over the real numbers plus a symmetric bilinear real form A »B (inner product) such that: (1) There exists a vector A with A -A <0 . (2) An...