Neural network processing system using semiconductor memories an

Boots – shoes – and leggings

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

364258, 364251, 3642448, 364DIG1, G06F 900

Patent

active

055949169

ABSTRACT:
A data processing system has a memory for realizing large-scale and high-speed parallel distributed processing and, especially, a data processing system for neural network processing. The neural network processing system comprises: a memory circuit for storing neuron output values, connection weights, the desired values of outputs, and data necessary for learning; an input/output circuit for writing or reading data in or out of said memory circuit; a processing circuit for performing a processing for determining the neuron outputs such as the product, sum and nonlinear conversion of the data stored in said memory circuit, a comparison of the output value and its desired value, and a processing necessary for learning; and a control circuit for controlling the operation of the memory circuit, the input/output circuit and the processing circuit. The processing circuit includes at least one of an address, a multiplier, a nonlinear transfer function circuit and a comparator so that at least a portion of the processing necessary for determining the neuron output values such as the product of sum may be accomplished in parallel. Moreover, these circuits are shared among a plurality of neurons and are operated in a time sharing manner to determine the plural neuron output values. Still moreover, the aforementioned comparator compares the neuron output value determined and the desired value of the output in parallel.

REFERENCES:
patent: 4611299 (1986-09-01), Hori et al.
patent: 4797858 (1989-01-01), Wang et al.
patent: 4847755 (1989-07-01), Morrison et al.
patent: 4873672 (1989-10-01), Etoh et al.
patent: 4939696 (1990-07-01), Katsuo et al.
patent: 4955024 (1990-09-01), Pfeiffer
patent: 4974169 (1990-11-01), Engel
patent: 4994982 (1991-02-01), Duranton et al.
patent: 5005121 (1991-04-01), Nakada et al.
patent: 5010477 (1991-04-01), Omoda et al.
patent: 5023833 (1991-06-01), Baum
patent: 5140670 (1992-08-01), Chua et al.
patent: 5142665 (1992-08-01), Bigus
patent: 5163120 (1992-11-01), Childers et al.
patent: 5179680 (1993-01-01), Colwell
patent: 5239654 (1993-08-01), Ing-Simmon et al.
patent: 5301340 (1994-04-01), Cook
Sejnowski et al. "Parallel Networks that Learn to Pronounce English Text," Complex Systems 1, 1987, pp. 145-168.
Advanced Micro Devices, Memory Products Data Book, Jan. 1989, pp. 4-80, 4-81.
Eberhardt et al., "Design of Parallel Hardware Neural Network Systems from Custom Analog VLSI `Building Block` Chips", International Joint Conference of Neural Networks, Jun. 18-22, 1989, pp. II-183 to II-190.
Rumelhart et al. "Learning Representations by Back Propagating Errors", Nature, V. 323, Oct. 9, 1986, pp. 533-536.
Suzuki et al. "A Study of Regular Architectures for Digital Implementation of Neural Networks", 1989 IEEE International Symp. on Circuits and Systems, May 8-11, 1989, pp. 82-85.
Manuel, "Are Artificial Neural Networks Finally Ready for Market?", Electronics, Aug. 1988, pp. 85-88.
Holler et al. "An Electrically Trainable Artificial Network (ETANN) with 10240 `Floating Gate` Synapses", Proceedings of the International Annual and Conference on Neural Network, 1989, pp. 50-55.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Neural network processing system using semiconductor memories an does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Neural network processing system using semiconductor memories an, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Neural network processing system using semiconductor memories an will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-1396226

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.