Title :
A computing system of (modular) chips
Author :
Wang, Yiwen ; Salam, F.M.A.
Author_Institution :
Dept. of Comput. Eng., Minnesota Univ., Duluth, MN, USA
Abstract :
Various analog chips with digital on-chip learning capability are described. A system of four neural chips has been constructed. The chips and the system have passed the testing stage and have been utilized in various experiments in image processing, recognition, and association. A prototype system consisting of four chips has 289 neurons and can process sub-images of 17×17 resolution in less than 400 ns. Second generation designs of ANNs using the dendro-dendritic ANN (DANN) architecture and the usual feedback (Hopfield-type) architecture are discussed, and transient behavior measurement that confirms that the worst convergence time to the desired steady state in less than 400 ns are presented
Keywords :
analogue computer circuits; neural chips; ANNs; Hopfield-type; dendro-dendritic ANN; neural chips; on-chip learning; transient behavior; Image processing; Image recognition; Neural network hardware; Neurofeedback; Neurons; Prototypes; Semiconductor device measurement; State feedback; System testing; Time measurement;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.226912
