A Resource-Constrained Sensor Dynamic Compensation Using a Learning-from-Examples Approach

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.

[1]  Gabor Karsai,et al.  Smart Dust: communicating with a cubic-millimeter computer , 2001 .

[2]  O. Nelles.  Nonlinear System Identification , 2001 .

[3]  M. Weiser,et al.  Hot topics-ubiquitous computing , 1993 .

[4]  P. Crilly.  A quantitative evaluation of various iterative deconvolution algorithms , 1991 .

[5]  Ganapati Panda,et al.  An intelligent pressure sensor using neural networks , 2000, IEEE Trans. Instrum. Meas..

[6]  Dario Petri,et al.  An improved method for iterative identification of bandlimited linear systems , 1991, [1991] Conference Record. IEEE Instrumentation and Measurement Technology Conference.

[7]  S. Sathiya Keerthi,et al.  Building Support Vector Machines with Reduced Classifier Complexity , 2006, J. Mach. Learn. Res..

[8]  Yuh-Jye Lee,et al.  RSVM: Reduced Support Vector Machines , 2001, SDM.

[9]  D. Petri,et al.  Energy- Aware Signals Classification in Ad- hocWireless Sensor Networks , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.

[10]  Pasquale Daponte,et al.  ANN-based error reduction for experimentally modeled sensors , 2000, Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066].

[11]  Olivier Chapelle,et al.  Training a Support Vector Machine in the Primal , 2007, Neural Computation.

[12]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[13]  Bernhard Schölkopf,et al.  Building Sparse Large Margin Classifiers , 2005, ICML.

[14]  Alexander J. Smola,et al.  Learning with kernels , 1998 .

[15]  D. Puccinelli,et al.  Wireless sensor networks: applications and challenges of ubiquitous sensing , 2005, IEEE Circuits and Systems Magazine.

[16]  Ray Andraka,et al.  A survey of CORDIC algorithms for FPGA based computers , 1998, FPGA '98.

[17]  Michael Koch,et al.  Ubiquitous Computing , 2001, CSCW-Kompendium.

[18]  Andrea Boni,et al.  Low-Power and Low-Cost Implementation of SVMs for Smart Sensors , 2007, IEEE Transactions on Instrumentation and Measurement.

[19]  T. Daboczi,et al.  Multiparameter optimization of inverse filtering algorithms , 1995, Proceedings of 1995 IEEE Instrumentation and Measurement Technology Conference - IMTC '95.

[20]  D. Petri,et al.  Low-power and Low-cost Implementation of SVMs for Smart Sensors , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.