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Edge of chaos in reaction diffusion CNN model

Angela Slavova, Ronald Tetzlaff (2017)

Open Mathematics

In this paper, we study the dynamics of a reaction-diffusion Cellular Nonlinear Network (RD-CNN) nodel in which the reaction term is represented by Brusselator cell. We investigate the RD-CNN dynamics by means of describing function method. Comparison with classical results for Brusselator equation is provided. Then we introduce a new RD-CNN model with memristor coupling, for which the edge of chaos regime in the parameter space is determined. Numerical simulations are presented for obtaining dynamic...

Emotion learning: Solving a shortest path problem in an arbitrary deterministic environment in linear time with an emotional agent

Silvana P Etruseva (2008)

International Journal of Applied Mathematics and Computer Science

The paper presents an algorithm which solves the shortest path problem in an arbitrary deterministic environment with n states with an emotional agent in linear time. The algorithm originates from an algorithm which in exponential time solves the same problem, and the agent architecture used for solving the problem is an NN-CAA architecture (neural network crossbar adaptive array). By implementing emotion learning, the linear time algorithm is obtained and the agent architecture is modified. The...

Ensemble neural network approach for accurate load forecasting in a power system

Krzysztof Siwek, Stanisław Osowski, Ryszard Szupiluk (2009)

International Journal of Applied Mathematics and Computer Science

The paper presents an improved method for 1-24 hours load forecasting in the power system, integrating and combining different neural forecasting results by an ensemble system. We will integrate the results of partial predictions made by three solutions, out of which one relies on a multilayer perceptron and two others on self-organizing networks of the competitive type. As the expert system we will apply different integration methods: simple averaging, SVD based weighted averaging, principal component...

Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays

Qianhong Zhang, Lihui Yang, Daixi Liao (2011)

International Journal of Applied Mathematics and Computer Science

Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.

Existence, uniqueness and global asymptotic stability for a class of complex-valued neutral-type neural networks with time delays

Manchun Tan, Desheng Xu (2018)

Kybernetika

This paper explores the problem of delay-independent and delay-dependent stability for a class of complex-valued neutral-type neural networks with time delays. Aiming at the neutral-type neural networks, an appropriate function is constructed to derive the existence of equilibrium point. On the basis of homeomorphism theory, Lyapunov functional method and linear matrix inequality techniques, several LMI-based sufficient conditions on the existence, uniqueness and global asymptotic stability of equilibrium...

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