Design and analysis of a novel chaotic diagonal recurrent neural network

DOI10.1016/J.CNSNS.2015.01.021zbMath1440.92007OpenAlexW2012859485MaRDI QIDQ2297461

Yanyan Li

Publication date: 20 February 2020

Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cnsns.2015.01.021

zbMATH Keywords

chaos controlchaotic neural networkweight convergenceadaptive learning algorithm

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Chaos control for problems involving ordinary differential equations (34H10)

Related Items (2)

Weak and strong convergence analysis of Elman neural networks via weight decay regularization ⋮ Nonlinear damped oscillators on Riemannian manifolds: numerical simulation

Cites Work

• On the global output convergence of a class of recurrent neural networks with time-varying inputs
• Partial state feedback control of chaotic neural network and its application
• Associative dynamics in a chaotic neural network.
• Cryptography based on delayed chaotic neural networks
• Chaotic neural networks with reinforced self-feedbacks and its application to \(N\)-queen problem
• A novel GCM chaotic neural network for information processing
• Effects of correlation among stored patterns on associative dynamics of chaotic neural network
• Global searching ability of chaotic neural networks

This page was built for publication: Design and analysis of a novel chaotic diagonal recurrent neural network