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Stochastic neural network

Stochastic neural networks are a type of artificial neural networks built by introducing random variations into the network, either by giving the… 
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Related topics

Related topics

8 relations
Artificial neural networkArtificial neuronBoltzmann machineMaxima and minima

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
Relaxed passivity conditions for discrete-time stochastic delayed neural networks
In this paper, the passivity problem is researched for discrete-time stochastic neural networks with time-varying delay. By… 
2011
2011
LMI Conditions for Robust Stability Analysis of Stochastic Hopfield Neural Networks with Interval Time-Varying Delays and Linear Fractional Uncertainties
In this paper, the delay-dependent robust stability for a class of stochastic neural networks with linear fractional… 
2010
2010
Exponential Stability of Uncertain Stochastic Neural Networks with Markovian Switching
This paper is concerned with the exponential stability analysis problem for a class of uncertain stochastic neural networks with… 
Highly Cited
2010
Highly Cited
2010
Asymptotic Stability of Stochastic Delayed Recurrent Neural Networks with Impulsive Effects
In this paper, the asymptotic stability for a class of stochastic neural networks with time-varying delays and impulsive effects… 
2008
2008
Impact of Fixed Boundary Conditions on the Basins of Attraction in the Flower's Morphogenesis of Arabidopsis Thaliana
Classically, theoretical studies focusing on biological systems are based on toric networks, which does not seem to be coherent… 
1996
1996
Pattern classification by stochastic neural network with missing data
In this paper, pattern classification by stochastic neural networks is considered. This model is also called a Gaussian mixture… 
1993
1993
Estimating A-Posteriori Probabilities using Stochastic Network Models
In this paper we present a systematic approach to constructing neural network classi ers based on stochastic model theory. A two… 
Highly Cited
1992
Highly Cited
1992
Scheduling for minimizing total actual flow time by neural networks
SUMMARY Scheduling problems are considered as combinatorial optimization problems. Hopfield and Tank (1985) showed that some… 
1989
1989
Learning in stochastic neural networks for constraint satisfaction problems
Researchers describe a newly-developed artificial neural network algorithm for solving constraint satisfaction problems (CSPs… 
1986
1986
Stochastic Dynamics of Neural Networks
The dynamics of stochastic neural networks are presented. The model is an algorithm based upon the assumption that the activities… 
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