3 April 2008 Performance evaluation of a FPGA implementation of a digital rotation support vector machine
Author Affiliations +
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Horacio Lamela, Jesús Gimeno, Matías Jiménez, Marta Ruiz, "Performance evaluation of a FPGA implementation of a digital rotation support vector machine", Proc. SPIE 6979, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI, 697908 (3 April 2008); doi: 10.1117/12.787475; https://doi.org/10.1117/12.787475
PROCEEDINGS
8 PAGES


SHARE
Back to Top