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In this paper, we address the problem of nonlinear sensor dynamic compensation that will be performed on board wireless sensor network nodes. To this aim, we design suitable reduced-complexity learning-from-example algorithms and implement them on resource-constrained devices, namely, 8-bit microcontrollers. The proposed approach is validated with simulations on different examples of nonlinear sensor...
In this paper we present a novel technique based on a learning-from-examples approach for dynamic compensation of sensors. The context of application is the area of Wireless Sensor Networks, where simple but at the same time efficient signal processing methods have to be implemented on local 8-bits microcontrollers.
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...
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