@article{(Open Science Index):https://publications.waset.org/pdf/15106,
	  title     = {Neural Network Implementation Using FPGA: Issues and Application},
	  author    = {A. Muthuramalingam and  S. Himavathi and  E. Srinivasan},
	  country	= {},
	  institution	= {},
	  abstract     = {.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. This paper discusses the issues involved in implementation of a multi-input neuron with linear/nonlinear excitation functions using FPGA. Implementation method with resource/speed tradeoff is proposed to handle signed decimal numbers. The VHDL coding developed is tested using Xilinx XC V50hq240 Chip. To improve the speed of operation a lookup table method is used. The problems involved in using a lookup table (LUT) for a nonlinear function is discussed. The percentage saving in resource and the improvement in speed with an LUT for a neuron is reported. An attempt is also made to derive a generalized formula for a multi-input neuron that facilitates to estimate approximately the total resource requirement and speed achievable for a given multilayer neural network. This facilitates the designer to choose the FPGA capacity for a given application. Using the proposed method of implementation a neural network based application, namely, a Space vector modulator for a vector-controlled drive is presented
},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {2},
	  number    = {12},
	  year      = {2008},
	  pages     = {2802 - 2808},
	  ee        = {https://publications.waset.org/pdf/15106},
	  url   	= {https://publications.waset.org/vol/24},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 24, 2008},
	}