DocumentCode
288631
Title
4×4×2 neural network design using modular neural chips with on-chip learning
Author
Oh, Hwa-Joon ; Salam, Fathi M A
Author_Institution
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
Volume
4
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
2070
Abstract
Describes a feedforward artificial neural network with learning capability in a modular design. The design uses a modified error backpropagation continuous-time learning rule. The modular design is implemented onto (identical) tiny chips where each chip implements a 4-input, 2-output modular network. The modular chips can then be cascaded in order to realize a large network by adding modular chips vertically and horizontally. The authors report on test results that demonstrate the successful operation of the chip and a constructed 4×4×2 neural network using three module chips
Keywords
backpropagation; feedforward neural nets; neural chips; 4×4×2 neural network; feedforward artificial neural network; modified error backpropagation continuous-time learning rule; modular neural chips; on-chip learning; Artificial neural networks; Circuits and systems; Equations; Laboratories; Network-on-a-chip; Neural network hardware; Neural networks; Neurons; Prototypes; Software testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374532
Filename
374532
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