chaotic systems are nonlinear dynamic systems, the main feature of which is high sensitivity to initial conditions. to initiate a design process in fuzzy model, chaotic systems must first be represented by t-s fuzzy models. in this paper, a new fuzzy modeling method based on sector nonlinearity approach has been recommended for chaotic systems relating to initial condition variations using the ...

different methods arising from scientific investigation for removing noise from chaotic signals have been introduced and one of their best is local projection approach. the local projection approach projects the chaotic data in the neighborhood onto the hyper-plane. selection of neighborhood radius has a direct impact on its performance. a noticeable feature associated with chaotic trajectories...

Abstract This paper discusses a novel “chaotic” form of superbanana transport, and compares theory to experiments on nonneutral plasmas. Superbanana transport is caused by particles that cross local trapping separatrices (magnetic or electric ripples) in the presence of field “errors” such as toroidal magnetic curvature. Traditionally, collisions (at rate ν) cause separatrix crossings, with res...

In this paper, chaotic dynamic and nonlinear control in a glucose-insulin system in types I diabetic patients and a healthy person have been investigated. Chaotic analysis methods of the blood glucose system include Lyapunov exponent and power spectral density based on the time series derived from the clinical data. Wolf's algorithm is used to calculate the Lyapunov exponent, which positive val...

study of the changes in the stock price in tehran stock exchange is of great importance. this is because of its application in forecasting the stock price in the stock exchange. the aim of this article is to investigate the forces and mechanisms that cause the dramatic changes in stock price and the formation of chaotic trend. to test whether the chaotic trend in the tehran stock exchange exist...

This paper introduces hybridization of particle swarm optimization (PSO) with genetic algorithm (GA) denoted as PSO+GA provides an efficient approach which is used to solve non linear chaotic datasets. The proposed algorithm employed in probabilistic neural network(PNN) which is a variant of radial basic function artificial neural network (RBFANN) for finding precise value spread factor for acc...