Asynchronous Pulse Neural Network Model for VLSI Implementation (Special Section on Nonlinear Theory and Its Applications)

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概要

• 論文の詳細を見る

• An asynchronous pulse neural network model which is suitable for VLSI implementation is proposed. The model neuron can function as a coincidence detector as well as an integrator depending on its internal time-constant relative to the external one, and show complex dynamical behavior includeing chaotic responses. A network with the proposed neurons can process spatio-temporal coded information through dynamical cell assemblies with functional synaptic connections.

• 社団法人電子情報通信学会の論文
• 1998-09-25

著者

• AIHARA Kazuyuki

  Graduate School of Engineering, The University of Tokyo

• Horio Yoshihiko

  Department Of Electronic Engineering Tokyo Denki University

• HANAGATA Mitsuru

  Department of Electronic Engineering, Tokyo Denki University

• Hanagata Mitsuru

  Department Of Electronic Engineering Tokyo Denki University

• Aihara Kazuyuki

  Graduate School Of Engineering The University Of Tokyo

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• Analog Hardware Implementation of a Mathematical Model of an Asynchronous Chaotic Neuron(Special Section on Analog Circuit Techniques and Relate)
• Nonlinear Resistor Circuits Using Capacitively Coupled Multi-Input MOSFETs
• Asynchronous Pulse Neural Network Model for VLSI Implementation (Special Section on Nonlinear Theory and Its Applications)
• A Neuronal Time Window for Coincidence Detection (Special Section on Nonlinear Theory and Its Applications)
• IC Implementation of a Switched-Current Chaotic Neuron (Special Section on Nonlinear Theory and Its Applications)

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