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Publication Type : Journal Article
Publisher : Journal of Telecommunications and Information Technology, National Institute of Telecommunications.
Source : Journal of Telecommunications and Information Technology, National Institute of Telecommunications, Volume 2016, Number 2, p.108-112 (2016)
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2016
Abstract : Modern communication systems require robust, adaptable and high performance decoders for efficient data transmission. Support Vector Machine (SVM) is a margin based classification and regression technique. In this paper, decoding of Bose Chaudhuri Hocquenghem codes has been approached as a multi-class classification problem using SVM. In conventional decoding algorithms, the procedure for decoding is usually fixed irrespective of the SNR environment in which the transmission takes place, but SVM being a machine-learning algorithm is adaptable to the communication environment. Since the construction of SVM decoder model uses the training data set, application specific decoders can be designed by choosing the training size efficiently. With the soft margin width in SVM being controlled by an equation, which has been formulated as a quadratic programming problem, there are no local minima issues in SVM and is robust to outliers. © 2016, National Institute of Telecommunications.
Cite this Research Publication : V. Sudharsan and Dr. Yamuna B., “Support vector machine based decoding algorithm for BCH codes”, Journal of Telecommunications and Information Technology, vol. 2016, pp. 108-112, 2016.