Foundations of fuzzy neural networks

Madan M. Gupta; Dandina Hulikunta Rao

doi:10.1117/12.165046

22 December 1993 Foundations of fuzzy neural networks

Madan M. Gupta, Dandina Hulikunta Rao

Proceedings Volume 2061, Applications of Fuzzy Logic Technology; (1993) https://doi.org/10.1117/12.165046
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

Abstract

Over the last decade or so, significant advances have been made in two distinct areas: fuzzy logic and computational neural networks. The theory of fuzzy logic provides mathematical strength to compare the uncertainties associated with human cognitive processes, such as thinking and reasoning. Also, it provides a mathematical morphology to emulate certain perceptual and linguistic attributes associated with human cognition. On the other hand, the computational neural network paradigm has evolved in the process of understanding the incredible learning and adaptability of biological neural mechanisms. Neural networks replicate, on a small scale, some of the computational operations observed in biological learning and adaptation. The integration of these two fields, fuzzy logic and neural networks, has given birth to an emerging paradigm--the fuzzy neural networks. The fuzzy neural networks have the potential to capture the benefits of the two fascinating fields, fuzzy logic and neural networks, into a single capsule. The intent of this paper is to provide an introductory look at this emerging research field of fuzzy neural networks.

Citation Download Citation

Madan M. Gupta and Dandina Hulikunta Rao "Foundations of fuzzy neural networks", Proc. SPIE 2061, Applications of Fuzzy Logic Technology, (22 December 1993); https://doi.org/10.1117/12.165046

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