Title :
A modular analog chip for feed-forward networks with on-chip learning
Author :
Oh, Hwa-Joon ; A. Salam, Fathi
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
A feedforward artificial neural network (ANN) with learning capability in modular design is presented using CMOS circuits. We employ a modified error backpropagation continuous-time learning rule. A (nonlinear) analog Gilbert multiplier is used as a synapse and a wide-range transconductance amplifier is used as soma. For learning circuits, the, same multiplier is used for updating the weights. Test results demonstrate the successful operation of the chip. Finally, a modular chip design for a large scale implementation of feedforward ANN with learning is described
Keywords :
CMOS analogue integrated circuits; analogue processing circuits; backpropagation; feedforward neural nets; large scale integration; neural chips; CMOS circuits; Gilbert multiplier; continuous-time learning rule; error backpropagation; feedforward artificial neural network; feedforward networks; large scale implementation; learning capability; modular analog chip; on-chip learning; soma; synapse; wide-range transconductance amplifier; Artificial neural networks; Circuit testing; Circuits and systems; Electronic mail; Equations; Feedforward systems; Laboratories; Large-scale systems; Network-on-a-chip; Neurons;
Conference_Titel :
Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-1760-2
DOI :
10.1109/MWSCAS.1993.342934
