نتایج جستجو برای: fuzzy neural networks
تعداد نتایج: 714687 فیلتر نتایج به سال:
This paper focuses on the problem of finite-time boundedness and finite-time passivity of discrete-time T-S fuzzy neural networks with time-varying delays. A suitable Lyapunov--Krasovskii functional(LKF) is established to derive sufficient condition for finite-time passivity of discrete-time T-S fuzzy neural networks. The dynamical system is transformed into a T-S fuzzy model with uncertain par...
in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of el...
Background & Aim: A main problem in diabetes is its timely and accurate diagnosis. This study aimed at diagnosing diabetes using data mining methods. Methods: The present study is an analytical investigation including 768 individuals with 8 attributes. Artificial neural networks and fuzzy neural networks were used to diagnose the diabetes. To achieve a real accuracy, the Kfold method was used ...
rivers and runoff have always been of interest to human beings. in order to make use of the proper water resources, human societies, industrial and agricultural centers, etc. have usually been established near rivers. as the time goes on, these societies developed, and therefore water resources were extracted more and more. consequently, conditions of water quality of the rivers experienced rap...
The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...
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...
In this paper we present an algorithm for automatic generation of fuzzy neural networks (FNN). Fuzzy neural networks are concept that integrates some features of the fuzzy logic and the artificial neural networks theory. Based on analysis of several different fuzzy neural networks models, uniform representation method is presented, and two basic types are identified: FNN based on perception fra...
This paper is concerned with the input-output-to-state stability for switched fuzzy neural networks. A new set of matrix norm based conditions is proposed such that switched fuzzy neural networks are input-output-to-state stable. A modified set of conditions for asymptotic stability of switched fuzzy neural networks is also presented in this paper. Keywords— input-output-to-state stability, swi...
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