Implementation of a New Neurochip Using Stochastic Logic

Shigeo Sato, Ken Nemoto, Shunsuke Akimoto, Mitsunaga Kinjo, Koji Nakajima

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)

Abstract

Even though many neurochips have been developed and investigated, the best suitable way for implementation has not been known clearly. Our approach is to exploit stochastic logic for various operations required for neural functions. The advantage of stochastic logic is that complex operations can be implemented with a few ordinary logic gates. On the other hand, the operation speed is not so fast since stochastic logic requires certain accumulation time for averaging. But huge integration can be achieved and its reliability is high because all of operations are done on digital circuits. Furthermore, we propose a nonmonotonic neuron realized by stochastic logic, since the nonmonotonic property is efficient for the performance enhancement in association and learning. In this paper, we show the circuit design and measurement results of a neurochip comprising 50 neurons are shown. The advantages of nonmonotonic property and stochasticism are shown clearly.

Original languageEnglish
Pages (from-to)1122-1127
Number of pages6
JournalIEEE Transactions on Neural Networks
Volume14
Issue number5
DOIs
Publication statusPublished - 2003 Sept

Keywords

  • Boltzmann machine (BM)
  • Large-scale integration (LSI) implementation
  • Nonmonotonic neuron
  • Simulated annealing
  • Stochastic logic
  • Traveling salesman problem

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