DocumentCode
1295383
Title
Mixed analogue-digital artificial-neural-network architecture with on-chip learning
Author
Schmid, A. ; Leblebici, Y. ; Mlynek, D.
Author_Institution
Dept. of Electr. Eng., Swiss Fed. Inst. of Technol., Lausanne, Switzerland
Volume
146
Issue
6
fYear
1999
fDate
12/1/1999 12:00:00 AM
Firstpage
345
Lastpage
349
Abstract
The authors present a novel artificial-neural-network architecture with on-chip learning capability. The issue of straightforward design-flow integration of an autonomous unit is addressed with a mixed analogue-digital approach, by implementing a charge-based artificial neural network which interacts with digital control and processing units. The circuit architecture and design-flow approach for the case of a Hamming network performing pixel-pattern recognition are described
Keywords
hardware description languages; integrated circuit design; learning (artificial intelligence); mixed analogue-digital integrated circuits; neural chips; reconfigurable architectures; Hamming network; autonomous unit; circuit architecture; design-flow integration; digital control; digital processing units; mixed analogue-digital artificial-neural-network architecture; on-chip learning; reconfigurable architecture;
fLanguage
English
Journal_Title
Circuits, Devices and Systems, IEE Proceedings -
Publisher
iet
ISSN
1350-2409
Type
jour
DOI
10.1049/ip-cds:19990685
Filename
819801
Link To Document