DocumentCode
1647692
Title
Implementation of learning in continuous analog circuitry
Author
Stüpmann, F. ; Rode, S. ; Schmidt, N. ; Geske, G.
Author_Institution
Neurosyst. GmbH, Rostock, Germany
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
733
Lastpage
736
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1005564
Filename
1005564
Link To Document