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Multilayer perceptron network techniques

Artificial neural networks (ANNs) are a non-linear function mapping technique that was initially developed to imitate the brain from both a structural and computational perspective. Its parallel architecture is primarily responsible for its computational power. The multilayer perceptron network architecture is probably the most popular and is used here. [Pg.435]

The most popular techniques of multilayer perceptrons (MLP) are back-propagation networks (Wythoff [1993] Jagemann [1998]). The weight matrixes W are estimated by minimizing the net error... [Pg.193]

See other pages where Multilayer perceptron network techniques is mentioned: [Pg.159]    [Pg.250]    [Pg.251]    [Pg.573]    [Pg.760]    [Pg.145]    [Pg.2408]    [Pg.234]    [Pg.235]    [Pg.240]    [Pg.427]    [Pg.93]    [Pg.215]    [Pg.268]    [Pg.667]    [Pg.254]    [Pg.475]   


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