Switched diffusion analog memory for neural networks with hebbian learning function and its linear operation

Hyosig Won, Yoshihiro Hayakawa, Koji Nakajima, Yasuji Sawada

研究成果: Conference article査読

2 被引用数 (Scopus)

抄録

We have fabricated a new analog memory for integrated artificial neural networks. Several attempts have been made to develop a linear characteristics of floating-gate analog memorys with feedback circuits. The learning chip has to have a large number of learning control circuit. In this paper, we propose a new analog memory SDAM with three cascaded TFTs. The new analog memory has a simple design, a small area occupancy, a fast switching speed and an accurate linearity. To improve accurate linearity, we propose a new charge transfer process. The device has a tunnel junction (poly-Si/poly-Si oxide/poly-Si sandwich structure), a thin-film transistor, two capacitors, and a floating-gate MOSFET. The diffusion of the charges injected through the tunnel junction are controlled by a source follower operation of a thin film transistor (TFT). The proposed operation is possible that the amounts of transferred charges are constant independent of the charges in storage capacitor.

本文言語English
ページ(範囲)746-751
ページ数6
ジャーナルIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
E79-A
6
出版ステータスPublished - 1996 6 1
イベントProceedings of the 1995 Joint Technical Conference on Circuits/Systems, Computers and Communications (JTC-CSCC'95) - Kanazawa, Jpn
継続期間: 1996 9 181996 9 21

ASJC Scopus subject areas

  • 信号処理
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • 電子工学および電気工学
  • 応用数学

フィンガープリント

「Switched diffusion analog memory for neural networks with hebbian learning function and its linear operation」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル