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Publication Type : Journal Article
Publisher : IOSRJEN
Source : IOSR Journal of Engineering (IOSRJEN), Volume 2, Issue 6, p.1352–1356 (2012)
Url : http://www.iosrjen.org/Papers/vol2_issue6%20(part-1)/N026135521356.pdf
Keywords : FPGA, Multi Layer Perceptron, Neuron, PLAN approximation, Sigmoid Activation.
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Verified : Yes
Year : 2012
Abstract : Artificial Neural Networks base their processing capabilities in a parallel architecture. This makes them extremely useful in pattern recognition, system identification and control problems. Multilayer Perceptron is an artificial neural network with one or more hidden layers. The Activation function determines the performance of a Multilayer Perceptron. In Multi Layer Perceptron, the most commonly used activation functions are sigmoid and bipolar sigmoid activation functions. In this paper we present a FPGA based digitalhardware implementation of Sigmoid and Bipolar Sigmoid Activation function. The digital hardware was designed for 32 bit fixed point arithmetic and was modeled using Verilog HDL. The synthesis tool used was Xilinx.
Cite this Research Publication : M. Panicker and Babu, C., “Efficient FPGA Implementation of Sigmoid and Bipolar Sigmoid Activation Functions for Multilayer Perceptrons”, IOSR Journal of Engineering (IOSRJEN), vol. 2, no. 6, pp. 1352–1356, 2012.