Stochastic analyses of the dynamics of generalized Little-Hopfield-Hemmen type neural networks
DOI10.1007/BF01025862zbMath0716.92001MaRDI QIDQ753698
Publication date: 1990
Published in: Journal of Statistical Physics (Search for Journal in Brave)
thermodynamic limitself-consistent equationfluctuation analysisGlauber dynamicsstochastic neural networksnonequilibrium phase transitionsnonlinear master equationasymmetric connectionN-body probability distributionpattern overlap fluctuationsStochastic analysessynaptic connectionssystem-size expansion
Neural networks for/in biological studies, artificial life and related topics (92B20) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Neural nets applied to problems in time-dependent statistical mechanics (82C32)
Cites Work
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- The Fokker-Planck equation. Methods of solution and applications
- Chemical oscillations, waves, and turbulence
- A biologically constrained learning mechanism in networks of formal neurons
- A cognitive and associative memory
- Neural networks: a biased overview.
- The existence of persistent states in the brain
- Collective properties of neural networks: A statistical physics approach
- Statistical Mechanics of Non-Equilibrium Systems. III: Fluctuation and Relaxation of Quantal Macrovariables
- Metastable states of neural networks incorporating the physiological Dale hypothesis
- Stochastic Dynamics of Neural Networks
- Transport, Collective Motion, and Brownian Motion
- Neural networks and physical systems with emergent collective computational abilities.
- Time-Dependent Statistics of the Ising Model
- Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements
- A logical calculus of the ideas immanent in nervous activity
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