M‐matrices and global convergence of discontinuous neural networks

DOI10.1002/cta.381zbMath1131.92004OpenAlexW1967374767MaRDI QIDQ5449725

Mauro Forti

Publication date: 18 March 2008

Published in: International Journal of Circuit Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cta.381

zbMATH Keywords

neural networkssliding modesglobal exponential convergenceconvergence in finite timediscontinuous neuron activations

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Stability of solutions to ordinary differential equations (34D20) Circuits, networks (94C99) Basic linear algebra (15A99)

Related Items (10)

Comparison of convergence and stability properties for the state and output solutions of neural networks ⋮ Global exponential convergence and global convergence in finite time of non-autonomous discontinuous neural networks ⋮ Almost periodicity for a class of delayed Cohen-Grossberg neural networks with discontinuous activations ⋮ Global convergence for Cohen-Grossberg neural networks with discontinuous activation functions ⋮ Dissipativity analysis and stabilization for discontinuous delayed complex-valued networks via matrix measure method ⋮ Generalized Lyapunov method for discontinuous systems ⋮ Existence and global stability of equilibrium point for delayed competitive neural networks with discontinuous activation functions ⋮ Dynamical behaviors of a class of recurrent neural networks with discontinuous neuron activations ⋮ Robust almost periodic dynamics for interval neural networks with mixed time-varying delays and discontinuous activation functions ⋮ Generalized stability for discontinuous complex-valued Hopfield neural networks via differential inclusions

Cites Work

• Unnamed Item
• Qualitative analysis of large scale dynamical systems

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