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Time Intervals Comparing Neural Network

Authors
Journal
Neural Networks
0893-6080
Publisher
Elsevier
Publication Date
Volume
9
Issue
7
Identifiers
DOI: 10.1016/0893-6080(96)00039-1
Keywords
  • Neural Network Model
  • Neuron-Like Element
  • Time-Interval Analysis
  • Time-Dependent Activity Channelling

Abstract

Abstract The proposed neuronal network model consisting of several tens of neuron-like elements with graded responses performs a continual analysis of differences (> 25 ms) in time intervals between successive input signals. The network comprises the following building blocks: clock, pattern developing modules, dynamic memory units, coincidence detectors, identifiers. Two types of network organization were developed: one with a loop of modules and another one with a cascade of modules. The activity of the proposed “neuronal” assembly can be channeled to different outputs—depending on whether the stimulus presentation is regular or random. The described computation mechanism can be involved in various time-dependent brain functions. Copyright © 1996 Elsevier Science Ltd

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