Towards a unified recurrent neural network theory: the uniformly pseudo-projection-anti-monotone net
DOI10.1007/S10114-011-0598-2zbMath1210.93039OpenAlexW2062010624MaRDI QIDQ2430906
Publication date: 8 April 2011
Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10114-011-0598-2
dynamicsunified theoryfeedback neural networksessential characteristicsuniformly pseudo-projection-antimonotone net
Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55) Artificial intelligence (68T99) Control/observation systems governed by ordinary differential equations (93C15) Stability theory for difference equations (39A30)
Cites Work
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- Information processing in three-state neural networks
- Decreasing energy functions as a tool for studying threshold networks
- Optimal and robust design of brain-state-in-a-box neural associative memories
- Global convergence and asymptotic stability of asymmetric Hopfield neural networks
- The existence of persistent states in the brain
- Collective Computation With Continuous Variables
- Analysis and synthesis of a class of neural networks: linear systems operating on a closed hypercube
- Learning grey-toned patterns in neural networks
- Winner-take-all cellular neural networks
- New conditions for global stability of neural networks with application to linear and quadratic programming problems
- Neural networks and physical systems with emergent collective computational abilities.
- Neurons with graded response have collective computational properties like those of two-state neurons.
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