Page 951 - The Mechatronics Handbook

32

Neural Networks

and Fuzzy Systems

32.1 Neural Networks and Fuzzy Systems
32.2 Neuron Cell
32.3 Feedforward Neural Networks
32.4 Learning Algorithms for Neural Networks
Hebbian Learning Rule • Correlation Learning
Rule • Instar Learning Rule • Winner Takes All
(WTA) • Outstar Learning Rule • Widrow–Hoff LMS
Learning Rule • Linear Regression • Delta Learning
Rule • Error Backpropagation Learning
32.5 Special Feedforward Networks
Functional Link Network • Feedforward Version of the
Counterpropagation Network • WTA
Architecture • Cascade Correlation Architecture • Radial
Basis Function Networks
32.6 Recurrent Neural Networks
Hopfield Network • Autoassociative
Memory • Bidirectional Associative Memories (BAM)
32.7 Fuzzy Systems
Fuzzification • Rule Evaluation • Defuzzification • Design
Example
32.8 Genetic Algorithms
Bogdan M. Wilamowski Coding and Initialization • Selection and Reproduction •
University of Wyoming Reproduction • Mutation

32.1 Neural Networks and Fuzzy Systems

New and better electronic devices have inspired researchers to build intelligent machines operating in a
fashion similar to the human nervous system. Fascination with this goal started when McCulloch and
Pitts (1943) developed their model of an elementary computing neuron and when Hebb (1949) intro-
duced his learning rules. A decade later Rosenblatt (1958) introduced the perceptron concept. In the early
1960s Widrow and Holf (1960, 1962) developed intelligent systems such as ADALINE and MADALINE.
Nillson (1965) in his book Learning Machines summarized many developments of that time. The pub-
lication of the Mynsky and Paper (1969) book, with some discouraging results, stopped for some time the
fascination with artificial neural networks, and achievements in the mathematical foundation of the back-
propagation algorithm by Werbos (1974) went unnoticed. The current rapid growth in the area of neural
networks started with the Hopfield (1982, 1984) recurrent network, Kohonen (1982) unsupervised training
algorithms, and a description of the backpropagation algorithm by Rumelhart et al. (1986).

©2002 CRC Press LLC