Dynamic compensation of Nonlinear sensors by a learning-from-examples approach

被引：17

作者：

Marconato, Anna ^{[1
]}

Hu, Mingqing ^{[2
]}

Boni, Andrea ^{[1
]}

Petri, Dario ^{[1
]}

机构：

[1] Univ Trent, Dept Informat & Commun Technol, I-38100 Trento, Italy

[2] Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China

来源：

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 2008年 / 57卷 / 08期

关键词：

dynamic compensation; low power; microcontroller implementation; reduced-set methods; support vector machines for regression (SVRs); wireless sensor networks (WSNs);

D O I：

10.1109/TIM.2008.922074

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 models.

引用

页码：1689 / 1694

页数：6

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