Stability analysis of discrete Hopfield neural networks with the nonnegative definite monotone increasing weight function matrix
DOI10.1155/2009/673548zbMath1178.39026OpenAlexW2157350522WikidataQ58647535 ScholiaQ58647535MaRDI QIDQ1040160
Mingdong Li, Xing Yin, Jun Li, Yong-Feng Diao
Publication date: 23 November 2009
Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)
Full work available at URL: https://eudml.org/doc/227387
Neural networks for/in biological studies, artificial life and related topics (92B20) Stability theory of functional-differential equations (34K20) Discrete version of topics in analysis (39A12) Stability theory for difference equations (39A30)
Related Items (2)
Cites Work
- Existence and global exponential stability of periodic solution for delayed high-order Hopfield-type neural networks
- Existence and stability of periodic solutions of high-order Hopfield neural networks with impulses and delays
- Decreasing energy functions as a tool for studying threshold networks
- Global convergence and asymptotic stability of asymmetric Hopfield neural networks
- Existence and global stability of periodic solution for delayed discrete high-order Hopfield-type neural networks
- Anti-periodic solutions for high-order Hopfield neural networks
- Global asymptotic and robust stability of recurrent neural networks with time delays
- Global exponential stability and periodic solutions of delay Hopfield neural networks
- Neural networks and physical systems with emergent collective computational abilities.
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