Fuzzy neural networks

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.

Grantor dc:publisher

Texas Tech University

Year dc:date.issued

1998

Author dc:creator

• Guven, Murat

• Artificial intelligence
• Neural networks (Computer science)
• Fuzzy sets
• Fuzzy algorithms

Statement dc:rights

• Unrestricted.

Language dc:language

eng

Identifier

http://hdl.handle.net/2346/22451

OAI identifier oai:identifier

oai:tdl-ir.tdl.org:2346/22451