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Local Position Estimation Using an Artificial Neural Network Based Model with a Hardware Implementation

Abdullah, Embong and Rohani, Abu Bakar and Syahrulanuar, Ngah (2012) Local Position Estimation Using an Artificial Neural Network Based Model with a Hardware Implementation. In: International Conference on Computational Science and Information Management (ICoCSIM), 3-5 December 2012 , Toba Lake, North Sumatera, Indonesia. pp. 223-226..

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Abstract

Efficient implementation of the activation function is an important part in the hardware design of artificial neural network. Sigmoid function is one of the most widely used activation function. In this paper, an efficient architecture for digital hardware implementation of sigmoid function is presented. The proposed method used second order nonlinear function (SONF) as a foundation and further improves the result by using 320 bits of read only memory (ROM) for storing a differential lookup table (differential LUT). The method proves to be more effective considering the smallest deviation of sigmoid function achieved in comparison to conventional LUT and SONF. Employing this method for hardware-based ANN in the indoor positioning system have shown that, ANN can detect the target position almost as accurate as software implementation with a speed 13 times faster. Thus the proposed idea is suitable to be implemented in a hardware-based ANN for various real-time applications.

Item Type: Conference or Workshop Item (Speech)
Additional Information: Proceedings of the First International Conference on Computational Science and Information Management (ICoCSIM2012) ISBN 978-967-0120-60-7 Vol. 1
Uncontrolled Keywords: Local positioning; Artificial neural network; Sigmoid function; Second order nonlinear function and differential lookup table
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: NOR NADIA SHAHIDA ZAKRIA
Date Deposited: 10 Jul 2013 07:49
Last Modified: 02 May 2018 06:54
URI: http://umpir.ump.edu.my/id/eprint/3663
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