Ways to Obtain Training Sample in Inversible System of Neural Network

Shao Song Wan; Jian Cao

doi:10.4028/www.scientific.net/AMM.373-375.1135

Paper Titles

Object Tracking Algorithm Based on Camshift Combining Background Subtraction with Three Frame Difference
p.1116

Application of Expert Decision Support System in Demonstration Engineering Project of Housing
p.1120

Robust PID Parameters Optimization Design Based on Improved Particle Swarm Optimization
p.1125

Particle Swarm Optimization with Crossover Operator for Global Optimization Problems
p.1131

Ways to Obtain Training Sample in Inversible System of Neural Network
p.1135

Framework for Emergency Decision Exercise System of Urban Crisis Based on Wargaming
p.1139

Research on Vehicle Path Planning Based on the BDD in the Uncertain Environment
p.1144

A Improved Particle Swarm Optimization and its Application in the Parameter Estimation
p.1150

Application of Improved Back Propagation Neural Network for the Recognition of Composite Insulator Hydrophobicity Grade
p.1155

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 373-375Ways to Obtain Training Sample in Inversible...

Ways to Obtain Training Sample in Inversible System of Neural Network

Abstract:

This paper discusses training structure and procedure about inversible system of neural network. Subsequently, selection of training sample is focused on. Finally, the paper proposes some principles and ways to obtain training sample of inversible system.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 373-375)

Pages:

1135-1138

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.373-375.1135

Citation:

Cite this paper

Online since:

August 2013

Authors:

Shao Song Wan, Jian Cao

Keywords:

Derivative, Inversible System, Sample, Signals

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Dai Xiangzhong, Zhang Kaifeng, Zhang Teng, in: ANN Generalized Inversion Control of Turbo-Generator Governor. IEEE Proceedings-Generation, Transmission and Distribution, 2009, 151(3): 327~333.

DOI: 10.1049/ip-gtd:20040380

Google Scholar

[2] Gulnur Birol, Cenk Undey, Ali Cinar, in: A Modular Simulation package for fed-batch fermentation: penicillin production. Computers and Chemical Engineering, 2010, Vol. 26: 1553~1565.

DOI: 10.1016/s0098-1354(02)00127-8

Google Scholar

[3] Xiangzhong Dai, Kaifeng Zhang, Xiang Lu, in: An improved ANN-inversion TCSC controllerbased on local measurements. IEEE Power Engineering Society 2012 General Meeting, Toranto, Canada, Vol. 4, 2555~2560.

DOI: 10.1109/pes.2003.1271046

Google Scholar

[4] Wangcheng Wang, Xiangzhong Dai, in: An Interactor algorithm for invertibility in generalnonlinear system. Proceedings of the 5th IEEE World Congress on Intelligent Control and Automation, Vol. 1, 59~63, June, 2011, Hangzhou, China Automation, Vol. 1, 59~63, June, 2011, Hangzhou, China.

DOI: 10.1109/wcica.2004.1340484

Google Scholar

[5] Ken Fujimoto and Toshiharu Sugie, in: Freedom in coordinate transformation for exact linearization and its application to transient behavior improvement. Automatica, 2011, 37(2): 137~144.

DOI: 10.1016/s0005-1098(00)00134-5

Google Scholar

[6] M. D. Di Benedetto and P. Lucibello, in: Inversion of nonlinear time-varying system. IEEE Trans. Automat. Contr., (2009).

DOI: 10.1109/9.233163

Google Scholar