Fuzzy neural networks

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Title: Fuzzy neural networks
Author: Guven, Murat
Abstract: Since the development of computer technology , methods have been developed and investigated to mimic the processes of the human brain . The human brain is a collection of billions of neurons interconnected with each other . Interconnected neurons are modeled with artificial neural networks (ANNs or NNs ) . Neural networks , mathematically speaking , are a system of linked parallel equations that are solved simultaneously and iteratively . Initial research can be found in papers by McCulloch -Pitts (1943 ) , Hebb (1949 ) , Rosenblatt (1958 ) , Minsky -Papert (1969 ) , and Hopfield (1982 ) . Since 1982 , research into neural networks has exploded and the use of neural networks to solve complex nonlinear problems has expanded (from pattem recognition to actual learning to playing games ) . Many different neural network architectures (the feedforward network , CMAC , Hopfield network , Kohonen network ) have been developed to aid in the solution of these problems . In this paper , we are interested in the feedforward network .
URI: http : / /hdl .handle .net /2346 /22451
Date: 1998-12


Fuzzy neural networks. Master's thesis, Texas Tech University. Available electronically from http : / /hdl .handle .net /2346 /22451 .

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