Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition

  • Simei Gomes Wysoski
  • Lubica Benuskova
  • Nikola Kasabov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)


This paper presents a novel on-line learning procedure to be used in biologically realistic networks of integrate-and-fire neurons. The on-line adaptation is based on synaptic plasticity and changes in the network structure. Event driven computation optimizes processing speed in order to simulate networks with large number of neurons. The learning method is demonstrated on a visual recognition task and can be expanded to other data types. Preliminary experiments on face image data show the same performance as the optimized off-line method and promising generalization properties.


Face Recognition Learning Procedure Similarity Threshold False Acceptance Rate False Rejection Rate 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Simei Gomes Wysoski
    • 1
  • Lubica Benuskova
    • 1
  • Nikola Kasabov
    • 1
  1. 1.Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand

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