DocumentCode
2565416
Title
A reconfigurable CMOS neural network
Author
Graf, H.P. ; Henderson, Dale
Author_Institution
AT&T Bell Lab., Holmdel, NJ, USA
fYear
1990
fDate
14-16 Feb. 1990
Firstpage
144
Lastpage
145
Abstract
An analog CMOS neural net with a programmable architecture containing 32 K connections is discussed. The objective of packing as large a network as possible on a chip leads to the choice of an analog approach. Analog signals are used only inside the network. All the input and output data are digital. The reconfigurable network consists of building blocks that can be joined to form various network architectures. The circuit can be programmed to implement single-layer networks or multilayer networks with binary or analog connections.<>
Keywords
CMOS integrated circuits; analogue computer circuits; neural nets; analog CMOS neural net; multilayer networks; programmable architecture; reconfigurable network; single-layer networks; Analog computers; Circuits; Concatenated codes; Current supplies; Mirrors; Neural networks; Neurons; Registers; Switches; Wire;
fLanguage
English
Publisher
ieee
Conference_Titel
Solid-State Circuits Conference, 1990. Digest of Technical Papers. 37th ISSCC., 1990 IEEE International
Conference_Location
San Francisco, CA, USA
Type
conf
DOI
10.1109/ISSCC.1990.110168
Filename
110168
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