Analysis to two Detecting Methods of non-linear analogue quantity

被引：0
作者：
Chen, Gang [1 ]
Wang, Erzhi [2 ]
Sun, Bo [2 ]
机构：
[1] Shenyang Ligong Univ, Fac Informat Sci & Engn, Shenyang, Peoples R China
[2] Shenyang Univ Technol, Fac Elect Engn, Shenyang, Peoples R China
来源：
ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL II, PROCEEDINGS | 2009年
关键词：
artificial neuron; non-linear analogue detection; embedded system; error analysis; STABILITY; NETWORKS; SYSTEMS;
D O I：
10.1109/ICICTA.2009.325
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
in the embedded distribution control system, the analogue quantity under test is usually non-linear. In this paper, the concept pf variable threshold neuron for the detecting of non-linear analogue is adopted. The subsection linearization and subsection variable slope are chosen as its training methods. It is shown by analyzing and comparing for the two training methods that the subsection linearization training method can improves the detecting precision and detecting resolution, and the subsection variable slope training method can not only calibrate the detecting curve from the subsection linearization ones but also give less computation error than it. Their simulation results are provided, and precise and feasible measurement is realized.
引用
收藏
页码：371 / +
页数：2
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