The TOPSIS process is one of the most comprehensive systems designed for decision making with multiple criteria, since this technique enables formulation of the problem as decision matrix, as well as the possibility of considering different quantitative and qualitative criteria in the problem. Fuzzy TOPSIS methods have been introduced to make fundamental decisions that make decisions decisions ...

The four-dimensional Hodgkin–Huxley equations describe the propagation in space and time of the action potential v(z) along a neural axon with z = x+ ct and c being the pulse speed. The potential v(z), which is parameterized by the temperature, is driven by three gating functions, m(z), n(z) and h(z), each of which obeys formal first order kinetics with rate constants that are represented as no...

This paper investigates the scope of usage of fuzzy logic to beat the effect of multiple access interference (MAI) through block parallel interference cancellation (BPIC) in a synchronous Carrier Interferometry/MC-CDMA uplink system. The users are classified in different blocks like very strong, strong, weak and very weak based on fuzzy membership function derived from the magnitude of the rece...

This tutorial paper presents an annotated overview of existing hardware implementations of Artificial Neural Systems based on “Pulse Stream” modulations. Pulse Streams are quasi-periodic binary waveforms which convey analog information on waveform timing. The theoretical bases of Pulse Stream computation are shown for the major techniques, and basic circuits are briefly described for most Neura...

In this paper fuzzy piecewise cubic interpolation is constructed for fuzzy data based on B-spline basis functions. We add two new additional conditions which guarantee uniqueness of fuzzy B-spline interpolation.Other conditions are imposed on the interpolation data to guarantee that the interpolation function to be a well-defined fuzzy function. Finally some examples are given to illustrate the...

Kernel methods and rough sets are two general pursuits in the domain of machine learning and intelligent systems. Kernel methods map data into a higher dimensional feature space, where the resulting structure of the classification task is linearly separable; while rough sets granulate the universe with the use of relations and employ the induced knowledge granules to approximate arbitrary conce...

This paper considers dissimilarity measures and clustering techniques for two special cases of set-defined objects: fuzzy granules and subsequence time series. To deal with clustering of such kind of objects, we propose two implementations that generalize the Fuzzy C-Means algorithm to granular feature spaces. Granular computing is a paradigm oriented towards capturing and processing meaningful...

The paper presents a novel type of fuzzy sets, called time-Varying Fuzzy Sets (VFS). These fuzzy sets are based on the Gaussian membership functions, they are depended on the error and they are characterized by the displacement of the kernels to both right and left side of the universe of discourse, the two extremes kernels of the universe are fixed for all time. In this work we focus only on t...

A new computational method based on Wilson wavelets is proposed for solving a class of nonlinear stochastic It^{o}-Volterra integral equations. To do this a new stochastic operational matrix of It^{o} integration for Wilson wavelets is obtained. Block pulse functions (BPFs) and collocation method are used to generate a process to forming this matrix. Using these basis functions and their operat...

For two-dimensional (2-D) digital filters implemented by a block recursive equation, explicit relations between their frequency characteristics and those of scalar filter are obtained. Specifically, these include the relation between the discrete-time Fourier transform (DTFT) of the block recursive equation and that of the scalar 2-D difference equation, and the relation between the block matri...