Research in VLSI System Implementation of Neuromorphic Learning Networks.

Abstract

The methodology of the researchers was to build experimental prototype learning systems they wanted: to develop a prototype of an enhanced neuron/synapse chip using some ideas that they have gained from existing chips, develop a prototype VME based experimental platform for the above devices, write experimental prototype system software to run the above prototype boards and chips as co-processors for typical computer system such as a SUN4 and develop new algorithms to perform other types of learning suitable for prototype VLSI implementation. The following results were achieved: System Level Hardware- redesigned prototype learning chips were fabricated, System Level Software- software modules to interface with their prototype system has has been written, Algorithms-theoretical and simulation experiments were carried out to gauge the efficiency of one-weight-at-a-time vs. parallel perturbations

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Document Details

Document Type
Technical Report
Publication Date
Oct 31, 1994
Accession Number
ADA278247

Entities

People

  • Joshua Alspector

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Analog Signals
  • Computer Programs
  • Computers
  • Contracts
  • Control Simulators
  • Digital Computers
  • Efficiency
  • Learning
  • Neural Networks
  • Perturbations
  • Prototypes
  • Simulations
  • Simulators
  • System Software

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Parallel and Distributed Computing.
  • Software Engineering.