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Stochastic analyses of the dynamics of generalized Little-Hopfield-Hemmen type neural networks
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Outgoing claims: the papers this work cites, builds on, or argues with.
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The Existence of Persistent States in the Brain
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Fluctuation and relaxation of macrovariables
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Glauber dynamics of the Little-Hopfield model
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Kinetic equations and time correlation functions of critical fluctuations
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The existence of persistent states in the brain
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Statistical mechanics of neural networks
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H-theorem and stability analysis for mean-field models of non-equilibrium phase transitions in stochastic systems
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Irreversible circulation and the undamped spiking in lasers
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Stochastic Processes in Physics and Chemistry
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Associative neural network model for the generation of temporal patterns. Theory and application to central pattern generators
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Time-Dependent Statistics of the Ising Model
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Neural networks and physical systems with emergent collective computational abilities.
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Sequential state generation by model neural networks.
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The van Hemmen model-a true spin glass?
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Metastable states of neural networks incorporating the physiological Dale hypothesis
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Spin-glass models of neural networks
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Collective computational properties of neural networks: New learning mechanisms
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Dynamical behavior of stochastic systems of infinitely many coupled nonlinear oscillators exhibiting phase transitions of mean-field type:Htheorem on asymptotic approach to equilibrium and critical slowing down of order-parameter fluctuations
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Continuous-time dynamics of asymmetrically diluted neural networks
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Dynamics of spin systems with randomly asymmetric bonds: Langevin dynamics and a spherical model
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Temporal sequences and chaos in neural nets
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Image evolution in Hopfield networks
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Evolution of a Nonlinear Ion Acoustic Wave
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Classical Spin-Glass Model
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Temporal Association in Asymmetric Neural Networks
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Asymmetric neural networks incorporating the Dale hypothesis and noise-driven chaos
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Theory of dynamic critical phenomena
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Order and chaos in neural systems: An approach to the dynamics of higher brain functions
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Stochastic Dynamics of Neural Networks
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A POWER SERIES EXPANSION OF THE MASTER EQUATION
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Dynamics of the Ising Model near the Critical Point. I
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Nonlinear Master Equation Approach to Asymmertrical Neural Networks of the Hopfield-Hemmen Type
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Transport, Collective Motion, and Brownian Motion
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Irreversible Circulation of Fluctuation
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Irreversible Circulation of Fluctuation
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Statistical Mechanics of Non-Equilibrium Systems. III: Fluctuation and Relaxation of Quantal Macrovariables
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Memory Dynamics in Asynchronous Neural Networks
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A Learning Algorithm for Boltzmann Machines*
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Noise-Driven Temporal Association in Neural Networks
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Modern Theory Of Critical Phenomena
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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The α‐parameter of autoassociative neural networks—Analysis of equilibrium states and network dynamics
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Study of self-inhibited analogue neural networks using the self-consistent signal-to-noise analysis
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Stochastic analysis of the dynamics of a general class of synchronous neural networks
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Recognition of temporal sequences of patterns using state-dependent synapses
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Self-consistent signal-to-noise analysis of the statistical behavior of analog neural networks and enhancement of the storage capacity
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Dynamics of associative memory with a general transfer function
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Associative memory based on synchronized firing of spiking neurons with time-delayed interactions
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Macroscopic dynamics in separable neural networks
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Statistical mechanics of stochastic neural networks: Relationship between the self-consistent signal-to-noise analysis, Thouless-Anderson-Palmer equation, and replica symmetric calculation approaches
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Statistical Physics of Neural Systems with Nonadditive Dendritic Coupling
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Dynamics of associative memory with a self-consistent noise
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Stochastic Analysis of Synchronous Neural Networks with Asymmetric Weights
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Critical dynamics and cyclic memory retrieval in non-reciprocal Hopfield networks
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