Title :
Implementation of learning in continuous analog circuitry
Author :
Stüpmann, F. ; Rode, S. ; Schmidt, N. ; Geske, G.
Author_Institution :
Neurosyst. GmbH, Rostock, Germany
fDate :
6/24/1905 12:00:00 AM
Abstract :
The chip described below is a self-learning classifier. The decision-making function is a trainable integrated analog neural network structure. The circuit not only contains the reproduction path, but also the learning on-chip. The process of weight change is fully integrated. The backpropagation algorithm is implemented in an analog circuit
Keywords :
CMOS analogue integrated circuits; analogue processing circuits; backpropagation; neural chips; neural net architecture; unsupervised learning; CMOS technology; backpropagation; continuous analog circuitry; decision-making function; forward-neuron; integrated analog neural network; learning on-chip; pattern classifier; self-learning; CMOS technology; Circuits; Electronic mail; Intelligent networks; Network topology; Neural networks; Neurons; Sensor arrays; Switches; Testing;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005564
