Analog CMOS current-mode implementation of the feedforward neural network with on-chip learning and storage

Author

Lan, Jeng-Feng ; Wu, Chung-Yu

Author_Institution

Dept. of Electron. Eng. & Inst. of Electron., Nat. Chiao Tung Univ., Hsinchu, Taiwan

Volume

1

fYear

1995

fDate

Nov/Dec 1995

Firstpage

645

Abstract

Based on the outstar structure and the ratio memory, a feedforward Hamming neural network with on-chip learning and storage is designed in CMOS current-mode circuits. The implemented feedforward net can be used as a pattern classifier. The chip of the feedforward Hamming net has been fabricated by 0.8 μm double-poly double-metal n-well CMOS process. The experimental results show that the ratio memory has the contrast enhancement characteristic. Also, the classifier can recognize the distorted pattern which is darken, brighten, level-shifted, or noisy of the exemplar pattern with gray level recognition capability

Keywords

CMOS analogue integrated circuits; analogue processing circuits; feedforward neural nets; integrated memory circuits; learning systems; neural chips; pattern classification; analog CMOS current-mode; double-poly double-metal n-well CMOS; feedforward Hamming net; feedforward neural network; neural chip; on-chip learning; on-chip storage; outstar structure; pattern classifier; ratio memory; CMOS memory circuits; CMOS process; Current mode circuits; Feedforward neural networks; Image storage; Master-slave; Network-on-a-chip; Neural networks; Neurons; Noise level; Pattern matching; Pattern recognition; Semiconductor device measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1995. Proceedings., IEEE International Conference on

Conference_Location

Perth, WA

Print_ISBN

0-7803-2768-3

Type

conf

DOI

10.1109/ICNN.1995.488256

Filename

488256