In this paper, we propose an efficient implementation of SVMs on a low-power and low-cost 8-bit microcontroller that can be applied to design smart sensors, sensor networks and in the area of pervasive computing, where intelligent data analysis is required, such as pattern classification, signal estimation and so on. A new model selection algorithm to extract the optimal number of free parameters and an optimized implementation which exploits the CORDIC algorithm are detailed and discussed with examples and simulation results.
Low-power and low-cost implementation of SVMs for smart sensors
Gasparini, Leonardo;
2005-01-01
Abstract
In this paper, we propose an efficient implementation of SVMs on a low-power and low-cost 8-bit microcontroller that can be applied to design smart sensors, sensor networks and in the area of pervasive computing, where intelligent data analysis is required, such as pattern classification, signal estimation and so on. A new model selection algorithm to extract the optimal number of free parameters and an optimized implementation which exploits the CORDIC algorithm are detailed and discussed with examples and simulation results.File in questo prodotto:
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