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… (More)
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Topic mentions per year

Topic mentions per year

1988-2017
0519882017

Papers overview

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2013
2013
One of the major challenges in neuroscience is to determine how noise that is present at the molecular and cellular levels… (More)
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2010
2010
In this paper, the asymptotic stability of the pinning synchronous solution of stochastic neural networks with and without time… (More)
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2003
2003
Recent advances in gene-expression profiling technologies provide large amounts of gene expression data. This raises the… (More)
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2003
2003
Hopfield (1984 Proc. Natl Acad. Sci. USA 81 3088–92) showed that the time evolution of a symmetric neural network is a motion in… (More)
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1997
1997
Unsupervised feature extraction by a stochastic neural network can be defined as a minimization of the redundancy between the… (More)
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1996
1996
This paper presents learning techniques for a novel feedforward stochastic neural network. The model uses stochastic weights and… (More)
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1995
1995
We describe E. Wong's stochastic neural network (1989) and show that it can be used, in principle, to perform analog optimization… (More)
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1995
1995
  • Petri Myllym
  • 1995
In this work, we are interested in the problem of nding maximum a posteriori probability (MAP) value assignments for a set of… (More)
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1995
1995
This paper presents two digital circuits that allow the implementation of a fully parallel stochastic Hopfield neural network… (More)
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1993
1993
Most theoretical investigations of large recurrent networks focus on the properties of the macroscopic order parameters such as… (More)
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