processes characterizing uncertainties needs the creating of the proper knowledge base for the controller. In this paper, to solve this problem the integration of fuzzy set theory and wavelet neural network (WNN) is considered. The structure and operation algorithms of fuzzy WNN based controller are presented. Using gradient method the learning of fuzzy WNN is performed to find optimal values o...

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

In this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and Newton-Cotesmethods with positive coefficient for the solution of linear Fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. Here neural network isconsidered as a part of large field called neural computing orsoft computing. We propose alearning algorithm from ...

in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...

as the t-wave section in electrocardiogram (ecg) illustrates the repolarisation phase of heart activity, the information which is accumulated in this section is so significant that can explain the proper operation of electrical activities in heart. long qt syndrome (lqt) and t-wave alternans (twa) have imperceptible effects on time and amplitude of t-wave interval. therefore, t-wave shapes of t...

In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized characterization Theorem. Then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. Here neural network is considered as a part of large eld called ne...

In this study, an adaptive neural-fuzzy analysis system is proposed for single-trial classification of motor imagery (MI) electroencephalogram (EEG) data. Associated with enhanced active segment selection and wavelet-fractal features, adaptive fuzzy neural network (AFNN) is used for the recognition of left and right MI data. In addition to continuous wavelet transform (CWT) and Student’s two-sa...