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> Hopfield model, programing stochastic update and adding noise levels
whitehat1
post Sep 27, 2007, 04:56 AM
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Hi, I am a student learning about neural networks and the first thing I had to do was to write a hopfield neural networks with asynchronous update then I have to modify that program so that it uses the stochastic update rule and noise but I'm lost a that could someone explain to me what is thata or how to achieve it

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lucid_dream
post Sep 27, 2007, 08:37 AM
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for the discrete case, asynchronous update means neural units do not get updated synchronously. Usually, the update is done by randomly picking a neural unit, which is likely what the stochastic update rule is referring to, but it could also be non-random (for example, by starting with neuron of index 1 and continuing until neuron n (in an n neuron network).
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D.R
post Oct 22, 2007, 03:22 PM
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The hopfield Neural Network, is simple it consists of single layer set of neurons called associative memory a hopfield network can store in its memory a sets of patterns for later use, the training algorithm is very simple for a computer implementation, later i will post an url with complete library for training patterns.


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