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

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.

[1]  R. Brereton,et al.  Support vector machines for classification and regression. , 2010, The Analyst.

[2]  Isabelle Guyon,et al.  Capacity control in linear classifiers for pattern recognition , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.