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Pattern Recognition Using Spiking Neurons and Firing Rates

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Advances in Artificial Intelligence – IBERAMIA 2010 (IBERAMIA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6433))

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Abstract

Different varieties of artificial neural networks have proved their power in several pattern recognition problems, particularly feed-forward neural networks. Nevertheless, these kinds of neural networks require of several neurons and layers in order to success when they are applied to solve non-linear problems. In this paper is shown how a spiking neuron can be applied to solve different linear and non-linear pattern recognition problems. A spiking neuron is stimulated during T ms with an input signal and fires when its membrane potential reaches a specific value generating an action potential (spike) or a train of spikes. Given a set of input patterns belonging to K classes, each input pattern is transformed into an input signal, then the spiking neuron is stimulated during T ms and finally the firing rate is computed. After adjusting the synaptic weights of the neuron model, we expect that input patterns belonging to the same class generate almost the same firing rate and input patterns belonging to different classes generate firing rates different enough to discriminate among the different classes. At last, a comparison between a feed-forward neural network and a spiking neuron is presented when they are applied to solve non-linear and real object recognition problems.

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Author information

Authors and Affiliations

  1. Escuela de Ingeniería - Universidad La Salle, Benjamín Franklin 47, Col. Condesa, CP, 06140, México

    Roberto A. Vázquez

Authors
  1. Roberto A. Vázquez
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Editors and Affiliations

  1. Departamento Académico de Computación, Instituto Tecnológico Autónomo de México, Río Hondo No. 1, 01000, Mexico, D.F., México

    Angel Kuri-Morales

  2. Department of Computer Science and Engineering, Universidad Nacional del Sur, Alem 1253, 8000, Bahía Blanca, Argentina

    Guillermo R. Simari

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Vázquez, R.A. (2010). Pattern Recognition Using Spiking Neurons and Firing Rates. In: Kuri-Morales, A., Simari, G.R. (eds) Advances in Artificial Intelligence – IBERAMIA 2010. IBERAMIA 2010. Lecture Notes in Computer Science(), vol 6433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16952-6_43

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  • DOI: https://doi.org/10.1007/978-3-642-16952-6_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16951-9

  • Online ISBN: 978-3-642-16952-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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