Neural computing with concurrent synchrony

Victor Parque Tenorio, Masakazu Kobayashi, Masatake Higashi

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Neural networks are important modeling tools to implement intelligent behaviour in a wide variety of phenomena. We introduce the concept of concurrent synchrony in spikes to enable the efficient representation of neural networks to process sensory stimuli. Using different sensory modalities, we show that information processing from stimuli can be represented compactly. This approach aims at introducing homeostasis into the behavior of neural populations in order to construct diverse and sophisticated control rules without increasing network complexity.

Original languageEnglish
Pages (from-to)304-311
Number of pages8
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8834
Publication statusPublished - 2014
Externally publishedYes

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Synchrony
Concurrent
Neural Networks
Neural networks
Homeostasis
Computing
Information Processing
Spike
Modality
Modeling
Concepts

Keywords

  • Concurrency
  • Neural representation
  • Spiking networks
  • Synchrony

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

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