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Chaotic Liquid State Machine

Author

Listed:
  • Mario Antoine Aoun

    (Computer Science Department, Faculty of Science, Université du Québec à Montréal, UQAM, Montréal, Canada)

  • Mounir Boukadoum

    (Computer Science Department, Faculty of Science, Université du Québec à Montréal, UQAM, Montréal, Canada)

Abstract

The authors implement a Liquid State Machine composed from a pool of chaotic spiking neurons. Furthermore, a synaptic plasticity mechanism operates on the connection weights between the neurons inside the pool. A special feature of the system's classification capability is that it can learn the class of a set of time varying inputs when trained from positive examples only, thus, it is a one class classifier. To demonstrate the applicability of this novel neurocomputing architecture, the authors apply it for Online Signature Verification.

Suggested Citation

  • Mario Antoine Aoun & Mounir Boukadoum, 2015. "Chaotic Liquid State Machine," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 9(4), pages 1-20, October.
    • Handle: RePEc:igg:jcini0:v:9:y:2015:i:4:p:1-20
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    Cited by:

    1. Minati, Ludovico & Bartels, Jim & Li, Chao & Frasca, Mattia & Ito, Hiroyuki, 2022. "Synchronization phenomena in dual-transistor spiking oscillators realized experimentally towards physical reservoirs," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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