Nonlinear dynamic compensation of sensors using inverse-model-based neural network

NCUIR > Research Center > Center for Complex Systems > journal & Dissertation > Item 987654321/35735

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/35735

Title:	Nonlinear dynamic compensation of sensors using inverse-model-based neural network
Authors:	Yu,Dongchuan;Liu,Fang;Lai,Pik-Yin;Wu,Aiguo
Contributors:	複雜系統研究中心
Keywords:	GAS-SENSING SYSTEMS;ITERATIVE DECONVOLUTION;NATURAL FREQUENCIES;FORCE SENSOR;IDENTIFICATION;DESIGN;OPTIMIZATION;ALGORITHMS;ARRAYS;MEMS
Date:	2008
Issue Date:	2010-07-07 15:50:16 (UTC+8)
Publisher:	中央大學
Abstract:	Many sensors (such as low-cost sensors), in essence, display strongly nonlinear dynamic behavior that cannot be calibrated by well-developed linear dynamic compensation methods. So far, no general nonlinear dynamic compensation (NLDC) method exists, altho
Relation:	IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT????
Appears in Collections:	[Center for Complex Systems] journal & Dissertation

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