Abstract: In this review paper a hardware implementation of an artificial neural network on Field Programmable Gate Arrays (FPGA) is presented. The parallel structure of a neural network makes it potentially fast for the computation of certain tasks. The same feature makes a neural network well suited for implementation in VLSI technology. Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. In this paper work of different researchers is presented so that it can help the young researchers in their research work.
Keywords: Artificial neural network, VHDL, Back propagation Algorithm, Xilinx FPGA, Sigmoid Activation Function.
Title: Artificial Neural Network Implementation on FPGA Chip
Author: Sahil Abrol, Mrs. Rita Mahajan
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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