Propagation and control of stochastic signals through universal learning networks

DOI10.1016/J.NEUNET.2005.10.005zbMath1103.68692OpenAlexW2011812968WikidataQ51955584 ScholiaQ51955584MaRDI QIDQ2507305

Shingo Mabu, Jinglu Hu, Kotaro Hirasawa

Publication date: 10 October 2006

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2005.10.005

zbMATH Keywords

neural networksgradient methodstochastic signalsprobabilistic networksnon-linear systemsforward propagation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Network design and communication in computer systems (68M10)

Related Items (5)

Stability analysis of recurrent neural networks with random delay and Markovian switching ⋮ Synchronization of discrete-time stochastic neural networks with random delay ⋮ Delay-distribution-dependent state estimation for discrete-time stochastic neural networks with random delay ⋮ Asymptotical mean square stability of Cohen-Grossberg neural networks with random delay ⋮ Synchronization of discrete-time complex networks with randomly occurring coupling and distributed time-varying delay

Cites Work

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• Nonlinear black-box modeling in system identification: A unified overview
• Optimal stochastic control
• Neural networks and physical systems with emergent collective computational abilities.
• A logical calculus of the ideas immanent in nervous activity

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