Recurrent neural network-based fuzzy logic system and method

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

395 3, 395 61, 395900, 395 21, 395 24, G06E 100, G06E 300, G06F 1518, G06G 700

Patent

active

058288120

ABSTRACT:
A recurrent, neural network-based fuzzy logic system includes in a rule base layer and a membership function layer neurons which each have a recurrent architecture with an output-to-input feedback path including a time delay element and a neural weight. Further included is a recurrent, neural network-based fuzzy logic rule generator wherein a neural network receives and fuzzifies input data and provides data corresponding to fuzzy logic membership functions and recurrent fuzzy logic rules.

REFERENCES:
patent: 5168549 (1992-12-01), Takagi et al.
patent: 5416888 (1995-05-01), Shimokawa
patent: 5479571 (1995-12-01), Parlos et al.
Keller, et al., "Fuzzy Logic Inference Neural Networks", SPIE, vol. 1192, pp. 582-591, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, 1989.
Cox, Earl, "Integrating Fuzzy Logic into Neural Nets", AI Expert, Jun. 1992, pp. 43-47.
Cela, et al., "Towards A Neural Fuzzy Controller", IEEE, Systems, Man, and Cybernetics, 1992 International, pp. 1277-1282.
Horikawa, et al., "On Fuzzy Modeling Using Fuzzy Neural Networks with the Back-Propagation Algorithm", IEEE, Transactions on Neural Networks, vol. 3, No. 5 Sep. 1992, pp. 801-806.
Sun, et al., "Fuzzy Modeling Based On Generalized Neural Networks And Fuzzy Clustering Objective Functions", IEEE, Proceedings of the 30th Conference on Decision and Control, Dec. 1991, Brighton, England, pp. 2924-2929.
Kawamura, et al., "A Prototype of Neuro-Fuzzy Cooperation System", IEEE International Conference On Fuzzy Systems, Mar. 8-12, 1992, San Diego, CA pp. 1275-1282.
Hamid R. Berenji, "Refinement of Approximate Reasoning-Based Controllers By Reinforcement Learning", Machine Learning: Proceedings of the Eighth International Workshop, Evanston, IL, Jun. 27-29, 1991 (5 pages).
Junhong Nie and D.A. Linkens, "Fuzzy Reasoning Implemented by Neural Networks", IEEE 1992, pp. II-702-II-707.
James J. Buckley, Yoichi Hayashi and Ernest Czogala, "On the Equivalence of Neural Networks and Fuzzy Expert Systems" IEEE 1992, pp. II-691-II-695.
D.E. Rumelhart, G.E. Hinton and R.J. Williams, "Learning Internal Representation By Error Propagation", 1986, Chapter 41, pp. 675-682.
E. Khan et al., "NeuFuz: Neural Network Based Fuzzy Logic Design Algorithms", Fuzz-IEEE '93 Proceedings, vol. 1, pp. 647-654 (Mar. 28-Apr. 1, 1993).
E.H. Mamdani, "Twenty Years of Fuzzy Control: Experiences Gained and Lessons Learnt", Fuzz-IEEE '93 Proceedings, vol. 1, pp. 339-344 (Mar. 28-Apr. 1, 1993).
Z. Kohavi, "Switching and Finite Automata Theory", McGraw-Hill, New York, 1978, pp. 322 and 323.
"National Semiconductor Looks To Marry Neural Networks and Fuzzy Control", Electronic Products, Aug. 1992, p. 21.
"System Writes Fuzzy Logic Automatically", Electronics, Jul. 27 1992, p. 4.
Gorrini, V. and Bersini, H. "Recurrent Fuzzy Systems" Proceedings of the Third IEEE Conference on Fuzzy Systems. pp. 193-198, Jun. 26, 1994.

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

Recurrent neural network-based fuzzy logic system and method does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Recurrent neural network-based fuzzy logic system and method, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Recurrent neural network-based fuzzy logic system and method will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-1620780

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