Neural network with selective error reduction to increase learni

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

G06F 1518

Patent

active

051290383

ABSTRACT:
An improved iterative learning machine having a plurality of multi-input/single-output signal processing units connected in a hierarchical structure includes a weight coefficient change control unit which controls weight change quantities for those multi-input/single-output signal processing units having iteratively reduced errors thereby increasing the learning speed, contrary to conventional learning machines which perform a learning operation in order to minimize a square error of multi-input/single-output signal processing units in the highest hierarchy of the hierarchical structure.

REFERENCES:
patent: 3601811 (1971-08-01), Yoshino
patent: 4912649 (1990-03-01), Wood
patent: 4912654 (1990-03-01), Wood
D. E. Rumelhart, G. E. Hinton and R. J. Williams: "Learning Representations by Back-Propagating Errors", Nature, vol. 323, pp. 533-536, Oct. 9, 1986.
Lippmann, "An Introduction to Computing with Nueral Nets", IEEE Acoustics, Speech, and Signal Processing Magazine, pp. 4-22, Apr. 1987.
Widrow, "Punish/Reward: Learning with a Critic in Adaptive Threshold Systems", IEEE Transactions on Systems, Man and Cybernetics, vol. SMC3, No. 5, pp. 455-465, Sep. 1973.

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 with selective error reduction to increase learni 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 with selective error reduction to increase learni, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Neural network with selective error reduction to increase learni will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-1836126

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