in this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the takagi-sugeno (t-s) fuzzy models is considered. a novel linear matrix inequality (lmi)-based stability criterion is obtained by using lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

anti-lock braking system (abs) is a nonlinear and time varying system including uncertainty, so it cannot be controlled by classic methods. intelligent methods such as fuzzy controller are used in this area extensively; however traditional fuzzy controller using simple type-1 fuzzy sets may not be robust enough to overcome uncertainties. for this reason an interval type-2 fuzzy controller is de...

Background and objectives: The kidneys of chronic kidney disease (CKD) patients do not have enough function and hemodialysis (HD) is a common procedure for their treatment. HD requires vascular access surgery (VAS) and arteriovenous fistula (AVF) is a low-complication method in VAS. However, different rates of AVF failure have been reported worldwide which can cause repeating s...

Problem statement: The purpose of this study was to compute fuzzy reliability and fuzzy availability of the serial process in butter-oil processing plant for various choices of failure and repair rates of sub-system. This plant consists of eight sub-systems out of which two are supported by standby units with perfect switch over devices and considered that these two sub-systems never fail. The ...

fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. in this paper, a modified method based on the comprehensive learning particle swarm optimization (clpso) is proposed for pixel classification in hsi color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...

Missing value is a challenging issue in data mining, as information deficiency negatively affects both data quality and reliability. This paper focuses on an algorithm of a fuzzy clustering approach for missing value imputation with noisy data immunity. The PCFKMI (Pre-Clustering based Fuzzy K-Means Imputation) method aggregates data instances to more accurate clusters for further appropriate e...

We construct a fuzzy varying coefficient bilinear regression model to deal with the interval financial data and then adopt the least-squares method based on symmetric fuzzy number space. Firstly, we propose a varying coefficient model on the basis of the fuzzy bilinear regression model. Secondly, we develop the least-squares method according to the complete distance between fuzzy numbers to est...

Adaptive fuzzy logic control systems with Gaussian membership functions are described. A systematic simulation study of 'dynamic focusing of awareness' in fuzzy logic control systems is provided. This study shows how the final steady-state values of the membership functions change in response to varying initial membership functions, changing desired trajectory, and varying system nonlinearities...

The paper investigates the robust control for uncertain Takagi–Sugeno (T–S) fuzzy systems with time-varying state and input delays. Delay-dependent stabilization criterion is proposed to guarantee the asymptotic stabilization of fuzzy systems with parametric uncertainties. The result of [Lee HJ, Park JB, Joo YH. Robust control for uncertain Takagi– Sugeno fuzzy systems with time-varying input d...

Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...