Modeling and Simulation of Backpropogation Algorithm Using VHDL
نویسندگان
چکیده
This paper deals with artificial neural network (ANN) architecture, the multilayer Feed-forward (MLFF) network with back propagation learning. The training of an artificial neural network involves two passes. In the forward pass, the input signals propagate from the network input to the output. In the reverse pass the calculated error signals propagate backwards through the network where they are used to adjust the weights. The calculation of output is carried out layer by layer in the forward direction. The weights of the output neuron layer are adjusted first since the target value of each output neuron is available to guide the adjustment of associated weights. The system is designed to detect the odd parity. In this particular set, it gives an output of logic ‘1’ when given inputs with odd parity and an output of logic ‘0’ when provided with inputs with even parity. Keywords— Back propagation, Artificial Neural Network (ANN), VHDL, Learning, Pattern Recognition (PR)
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