DocumentCode :
2400852
Title :
A Neuron- and a Synapse Chip for Artificial Neural Networks
Author :
Lansner, John A. ; Lehmann, Torsten
Author_Institution :
Comput. Neural Network Center, Tech. Univ. of Denmark, Lyngby, Denmark
fYear :
1992
fDate :
21-23 Sept. 1992
Firstpage :
213
Lastpage :
216
Abstract :
A cascadable, analog, CMOS chip set has been developed for hardware implementations of artificial neural networks (ANN´s):I) a neuron chip containing an array of neurons with hyperbolic tangent activation functions and adjustable gains, and II) a synapse chip (or a matrix-vector multiplier) where the matrix is stored on-chip as differential voltages on capacitors. In principal any ANN configuration can be made using these chips. A neuron array of 4 neurons and a 4 × 4 matrix-vector multiplier has been fabricated in a standard 2.4 μm CMOS process for test purposes. The propagation time through the synapse and neuron chips is less than 4 μs and the weight matrix has a 10 bit resolution.
Keywords :
CMOS integrated circuits; capacitors; matrix multiplication; multiplying circuits; neural chips; ANN configuration; CMOS chip set; artificial neural networks; capacitors; hardware implementations; hyperbolic tangent activation functions; matrix-vector multiplier; neuron chip; propagation time; size 2.4 mum; synapse chip; word length 10 bit; Artificial neural networks; Backpropagation algorithms; Bipolar transistors; CMOS process; Capacitors; Computer networks; Neurofeedback; Neurons; Testing; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Solid-State Circuits Conference, 1992. ESSCIRC '92. Eighteenth European
Conference_Location :
Copenhagen
Print_ISBN :
87-984232-0-7
Type :
conf
DOI :
10.1109/ESSCIRC.1992.5468235
Filename :
5468235
Link To Document :
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