This paper investigates some properties of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. First, we prove that there exists a unique solution of the T-S fuzzy Hopfield neural network. Second, we determine a condition for input-to-state stability (ISS) of the T-S fuzzy Hopfield neural network. These results will be useful to analyze dynamic behavior of fuzzy neural networks.

A fuzzy neural network and its relevant fuzzy neuron and fuzzy learning algorithm are introduced. An object-oriented implementation of fuzzy neural network in MATLAB environment is realized. Simulations are carried out by SIMULINK. The performance of fuzzy neural network is experimentally compared with other neural networks trained by backpropagation algorithms. It shows better convergence spee...

This article studies the global Mittag-Leffler stability of fractional order fuzzy cellular neural networks via hybrid feedback controllers. Based on control technique Lyapunov approach, and some novel analysis techniques calculation, sufficient conditions are obtained to guarantee Global Mittag-Lefflers stability. Finally, two simulation example given illustrate effectiveness proposed method.

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...

In this paper, linear matrix inequality (LMI) approach for synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete and unbounded distributed delays based on sampled-data controlis investigated. Lyapunov-Krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of...

Computational intelligence paradigm covers several approaches for technical problems solving in an intelligence manner, such as artificial neural networks, fuzzy logic systems, evolutionary computation, etc. Each approach provides engineers and researchers with the smart and powerful tools to handle various real-life concerns. Even more powerful tools were designed at the joint of different com...

We investigate the effectiveness of GP-generated intelligent structures in classification tasks. Specifically, we present and use four context-free grammars to describe (1) decision trees, (2) fuzzy rule-based systems, (3) feedforward neural networks and (4) fuzzy Petri-nets with genetic programming. We apply cellular encoding in order to express feedforward neural networks and fuzzy Petri-nets...

a novel neuro-based method is introduced to solve the laminar boundary layer and the turbulent free jet equations. the proposed method is based on cellular neural networks, cnns, which are recently applied widely to solve partial differential equations. the effectiveness of the method is illustrated through some examples.