backpropagation neural network


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BACK PROPAGATIONback propagation learning theory


BACK PROPAGATI ON LEARNI NG THEORY1Submitted to Presented by Submitted to Presented byDr. Vishal Sahani Puneet Kr SinghM.Tech(2ndsem)Full Time P K Singh , F O E , D E I http:/ / student_community.htmlBACKPROPAGATION NEURAL NETWORK One of the most commonly used supervised ANN model is back propagation network that uses back propagation learning algorithm. These elements or nodes are arranged into different layers: input, middle and output. The output from a back propagation neural network is computed using a procedure known as the forward pass2 P K Singh , F O E , D E I The input layer propagates a particular input vectors components to each node in the middle layer. Middle Layer nodes compute output values, which becomes input to the nodes of output layer. becomes input to the nodes of output layer. The output layer nodes compute the network output for the particular input vector.3P K Singh , F O E , D E IMulti-layer neural network using 4Multi-layer neural network using back propagationP K Singh , F O E , D E I5 P K Singh , F O E , D E IAr t ificia l Neu r on :Cla s s ica l Act iva t ion Fu n ct ion s( )z z =Li near act i vat i on Logi st i c act i vat i on( ) 11 zze =+zz16Thr eshol d act i vat i onHyper bol i c t angent act i vat i on( ) ( ) uueeu tanh u 2211+= =( ) 1, 0,sign ( )1, 0.if zz zif z > = =


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