Delta Learning Rule and Backpropagation Rule for Multilayer Perceptron

2019 
In a network, if the output values cannot be traced back to the input values and if for every input vector, an output vector is calculated, then there is a forward flow of information and no feedback between the layers. Such type of network is known as feedforward networks. This chapter discusses feedforward neural network, delta learning rule. Error back propagation algorithm for unipolar and bipolar activation function are included in this chapter. Matlab program for calculating output for a multilayer neural network using error back propagation algorithm is also given in the chapter.
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