An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation
In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and me...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-09-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/14/9/17353 |
| _version_ | 1798039285630238720 |
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| author | Honghang Yan Fang Deng Jian Sun Jie Chen |
| author_facet | Honghang Yan Fang Deng Jian Sun Jie Chen |
| author_sort | Honghang Yan |
| collection | DOAJ |
| description | In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition N and reduces the training time to 1 N and memory cost to 1 N , has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. |
| first_indexed | 2024-04-11T21:51:46Z |
| format | Article |
| id | doaj.art-e9fe75f6982440ea8e98b7d80271e2e9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:51:46Z |
| publishDate | 2014-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e9fe75f6982440ea8e98b7d80271e2e92022-12-22T04:01:13ZengMDPI AGSensors1424-82202014-09-01149173531737510.3390/s140917353s140917353An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear CompensationHonghang Yan0Fang Deng1Jian Sun2Jie Chen3School of Automation, Beijing Institute of Technology, Haidian District Zhongguancun South Street No. 5, Beijing 100081, ChinaSchool of Automation, Beijing Institute of Technology, Haidian District Zhongguancun South Street No. 5, Beijing 100081, ChinaSchool of Automation, Beijing Institute of Technology, Haidian District Zhongguancun South Street No. 5, Beijing 100081, ChinaSchool of Automation, Beijing Institute of Technology, Haidian District Zhongguancun South Street No. 5, Beijing 100081, ChinaIn this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition N and reduces the training time to 1 N and memory cost to 1 N , has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm.http://www.mdpi.com/1424-8220/14/9/17353decomposition algorithmdata amountFourier neural network nonlinear errors compensation |
| spellingShingle | Honghang Yan Fang Deng Jian Sun Jie Chen An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation Sensors decomposition algorithm data amount Fourier neural network nonlinear errors compensation |
| title | An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation |
| title_full | An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation |
| title_fullStr | An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation |
| title_full_unstemmed | An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation |
| title_short | An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation |
| title_sort | nn based srd decomposition algorithm and its application in nonlinear compensation |
| topic | decomposition algorithm data amount Fourier neural network nonlinear errors compensation |
| url | http://www.mdpi.com/1424-8220/14/9/17353 |
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