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
Link To Document :
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