Tytuł:

Support Vector Machine based Decoding Algorithm for BCH Codes, Journal of Telecommunications and Information Technology, 2016, nr 2

Autor:

Sudharsan, V. ; Yamuna, B.

Temat i słowa kluczowe:

Support Vector Machine ; BCH codes ; kernel ; Soft Decision Decoding ; coding gain ; multi-class classification ; Chase-2 algorithm

Opis:

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 machinelearning 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.

Wydawca:

National Institute of Telecommunications

Data wydania:

2016, nr 2

Typ zasobu:

artykuł

Format:

application/pdf

Identyfikator zasobu:

ISSN 1509-4553, on-line: ISSN 1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności