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machine learning - Spiking neural networks

Which is the book one should start with in the domain of spiking neural networks? I know about Gerstner's "Spiking Neuron Models", published in 2002. Is there a more recent book, or maybe a more suitable one? I have a background in maths and artificial neural networks.

If there are some good articles or overviews in this domain, also add them to the list.

Thanks.

LATER EDIT

Karel's answer:

" It depends what do you mean by spiking neural networks - there are at least several basic points of view. Gerstner represents the first one - he is focused on modelling of biological neurons. And his book from 2002 is really good starting point for understanding bio-physical models of neuron. It the past it was possible to find this book also in html ..

On the other hand by ¨Spiking neuron" in the computer science context is usually meant the SRMo model (Spike Response Model), which can be used also as an alternative to classical percepron-based networks.

This model is described very well in the works of Wolfgang Maass (http://www.igi.tugraz.at/maass/). He has focused on the computational power of the model and he compares the SRM model with percepron and RBF-unit.

If you want to use the model in a network I recommend to you works of Sander Bohte (http://homepages.cwi.nl/~sbohte/) who derived SpikeProp algorithm.

(I personally derived a variant of SpikeProp which was fast enough to be used for real-word applications.) "

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Spiking Neural Networks (SNNs) or Pulsed Neural Networks (PNNs) are artificial neural networks (ANNs) that more closely emulate the behaviours of natural neural mechanisms. I would like to advise you following fundamental books:

  • Fundamentals of Computational Neuroscience by Thomas Trappenberg
  • Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems by Peter Dayan
  • Spiking Neuron Models: Single Neurons, Populations, Plasticity by Wulfram Gerstner

I personally derived a variant of Remote Supervised Method (ReSuMe) which has better learning rate and morphological advantages compared to ReSuMe introduced by Filip Ponulak.

In the meantime, I would like to list some of simulator tools dealing with SNNs. Most of them which I played with are based on Python so please take into account that as well. There might be more others based on other languages.


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