Low-Power and Low-Cost Implementation of SVMs for Smart Sensors

In this paper, we propose an efficient implementation of support vector machines (SVMs) on a low-power and low-cost 8-bit microcontroller. The proposed solution can be advantageously used to implement smart sensors and sensor networks for intelligent data analysis and pervasive computing. A new model selection algorithm that allows fitting the resource constraints imposed by the hardware architecture is proposed. Moreover, the performance of an optimized implementation which exploits the CORDIC algorithm is detailed and discussed.