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World leading smartphone and mobile technology research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers from the Department of Computer & Information Sciences involved in researching exciting new applications for mobile and smartphone technology. But the transformative application of mobile technologies is also the focus of research within disciplines as diverse as Electronic & Electrical Engineering, Marketing, Human Resource Management and Biomedical Enginering, among others.

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Embedded SVM on TMS320C6713 for signal prediction in classification and regression applications

Zabalza, Jaime and Ren, Jinchang and Clemente, Carmine and Di Caterina, Gaetano and Soraghan, John (2012) Embedded SVM on TMS320C6713 for signal prediction in classification and regression applications. In: 2012 5th European DSP Education and Research Conference (EDERC). IEEE, pp. 90-94. ISBN 978-1-4673-4595-8

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Support Vector Machine (SVM) is a very powerful tool for signal prediction including classification and regression. With Texas Instruments TMS320C6713 DSK, an embedded SVM is implemented, where a user friendly interface is provided via peripherals like the DIPs and LEDs. The C6713 processor in combination with the SDRAM block memory can solve the complex computation that SVM requires. Also a Real-Time utilisation of the device from Matlab environment is demonstrated. An exciting application framework is finally obtained, from which some conclusions related to the implementation and final usage are derived.