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Proceedings Paper

Performance evaluation of a FPGA implementation of a digital rotation support vector machine
Author(s): Horacio Lamela; Jesús Gimeno; Matías Jiménez; Marta Ruiz
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Paper Abstract

In this paper we provide a simple and fast hardware implementation for a Support Vector Machine (SVM). By using the CORDIC algorithm and implementing a 2-based exponential kernel that allows us to simplify operations, we overcome the problems caused by too many internal multiplications found in the classification process, both while applying the Kernel formula and later on multiplying by the weights. We show a simple example of classification with the algorithm and analyze the classification speed and accuracy.

Paper Details

Date Published: 3 April 2008
PDF: 8 pages
Proc. SPIE 6979, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI, 697908 (3 April 2008); doi: 10.1117/12.787475
Show Author Affiliations
Horacio Lamela, Univ. Carlos III de Madrid (Spain)
Jesús Gimeno, Univ. Carlos III de Madrid (Spain)
Matías Jiménez, Univ. Carlos III de Madrid (Spain)
Marta Ruiz, Univ. Carlos III de Madrid (Spain)


Published in SPIE Proceedings Vol. 6979:
Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI
Harold H. Szu; F. Jack Agee, Editor(s)

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