ANALOG CIRCUIT DESIGN BASED ON NEURAL NETWORKS.

Yong B. Cho, Yoshiyasu Takefuji

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Neural networks have been studied for many years with the hope of achieving human-like performance in such fields as speech and image recognition. A recent resurgence has resulted from VLSI advances, neural network models, and learning algorithms. Neural networks are also very suitable in certain areas such as NP-complete constraint and satisfaction problems, due to the nature of parallel and distributed processing. Neural network models are composed of a mass of fairly simple computational elements and rich interconnections between the elements. Neural networks operate in a parallel and distributed fashion which may resemble biological neural networks. Behaviors of neurons and the strengths of synaptic interconnections are simulated by operational amplifiers and resistors respectively. Several examples are presented, including how to build neural network components based on analog circuits for simulating neural networks and conventional logic circuits.

本文言語English
ホスト出版物のタイトルProceedings of the Annual Southeastern Symposium on System Theory
出版社IEEE
ページ100-105
ページ数6
ISBN(印刷版)0818608471
出版ステータスPublished - 1988
外部発表はい

出版物シリーズ

名前Proceedings of the Annual Southeastern Symposium on System Theory

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 数学 (全般)

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