Objectives 4 Perceptron Learning Rule
contribution was the introduction of a learning rule for training perceptron networks to solve pattern recognition problems [Rose58]. ... terns into a finite number of classes. This is especially useful in such appli- ... th element of the network output vector as pa 1 AA n AA W AA b R x 1 S x R S x 1 S x 1 S x 1 Input RSAA AA AA a = hardlim
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Objectives 4 Perceptron Learning Rule - Martin Hagan
hagan.okstate.edu4 Perceptron Learning Rule 4-6, , . (4.10) The decision boundary is then. (4.11) This defines a line in the input space. On one side of the line the network output will be 0; on the line and on the other side of the line the output will
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