Application of Multi Layer Artificial Neural Network in the Diagnosis System: A Systematic Review

Arvind Singh Rawat, Arti Rana, Adesh Kumar, Ashish Bagwari


Basic hardware comprehension of an artificial neural network (ANN), to a major scale depends on the proficientrealization of a distinctneuron. For hardware execution of NNs, mostly FPGA-designed reconfigurable computing systems are favorable .FPGA comprehension of ANNs through a hugeamount of neurons is mainlyan exigentassignment. This workconverses the reviews on various research articles of neural networks whose concernsfocused in execution of more than one input neuron and multilayer with or without linearity property by using FPGA. An execution technique through reserve substitution isprojected to adjust signed decimal facts. A detailed review of many research papers have been done for the
proposed work.


FPGA, Neural Network, VHDL

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