Patent
1994-09-22
1995-12-26
MacDonald, Allen R.
395 22, 395 24, G06F 1518
Patent
active
054795796
ABSTRACT:
High-speed, analog, fully-parallel and asynchronous building blocks are cascaded for larger sizes and enhanced resolution. A hardware-compatible algorithm permits hardware-in-the-loop learning despite limited weight resolution. A computation-intensive feature classification application has been demonstrated with this flexible hardware and new algorithm at high speed. This result indicates that these building block chips can be embedded as application-specific-coprocessors for solving real-world problems at extremely high data rates.
REFERENCES:
patent: 4639619 (1987-01-01), Baldwin et al.
patent: 4906865 (1990-03-01), Holler
patent: 4961005 (1990-10-01), Salam
patent: 4972187 (1990-11-01), Wecker
patent: 4994982 (1991-02-01), Duranton et al.
patent: 4996648 (1991-02-01), Jourjine
patent: 5004932 (1991-04-01), Nejime
patent: 5045713 (1991-09-01), Shima
patent: 5047655 (1991-09-01), Chambost et al.
patent: 5053645 (1991-10-01), Harada
patent: 5063601 (1991-10-01), Hayduk
patent: 5068662 (1991-11-01), Guddanti et al.
patent: 5095443 (1992-03-01), Watanabe
patent: 5109275 (1992-04-01), Naka et al.
An Electrically Trainable Neural Network Jun. 1989 Mark Holler.
Design of parallel hardware neural network system Silvio Eberhardt Jun. 1989.
A Compact and General Purpose Neural Chip with Electrically Programmable Systems May 1990 IEEE.
Impleentation of Artificial Neural Networks Using Current Mode Analogue Current Techniques P. K. Houselander Feb. 1989.
A Neural Chips Survey by Tom J. Schwartz, AI Expert, Dec. 1990, pp. 34-39.
Fuzzy/Neural Split-Chip Personality by R. Colin Johnson, Electronics Engineering Times, Apr. 2, 1990.
How Neural Networks Learn From Experience by Geoffrey E. Hinton, Scientific American, Sep. 1992, pp. 145-151.
Daud Taher
Duong Tuan A.
Thakoor Anilkumar P.
Dorvil Richemond
Jones Thomas H.
Kusmiss John H.
MacDonald Allen R.
Miller Guy M.
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