Time-Frequency Analysis of Hot Rolling Using Manifold Learning
作者： Francisco J. García , Ignacio Díaz , Ignacio Álvarez , Daniel Pérez , Daniel G. Ordonez
DOI: 10.1007/978-3-642-23957-1_17
关键词:
摘要: In this paper, we propose a method to compare and visualize spectrograms in low dimensional space using manifold learning. This approach is divided two steps: data processing dimensionality reduction stage feature extraction visualization stage. The procedure applied on different types of from hot rolling process, with the aim detect chatter. Results obtained suggest future developments applications other industrial processes.
springer.com
core.ac.uk
springerlink.com参考文章(10)
Hongyuan Zha, Zhenyue Zhang, Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment arXiv: Learning. ,(2002)
Teuvo Kohonen, Self-Organizing Maps ,(1995)
Boualem Boashash, Time-Frequency Signal Analysis and Processing: A Comprehensive Reference ,(2015)
Joshua B Tenenbaum, Vin de Silva, John C Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction Science. ,vol. 290, pp. 2319- 2323 ,(2000) , 10.1126/SCIENCE.290.5500.2319
Sam T Roweis, Lawrence K Saul, Nonlinear Dimensionality Reduction by Locally Linear Embedding Science. ,vol. 290, pp. 2323- 2326 ,(2000) , 10.1126/SCIENCE.290.5500.2323
Zhenyue Zhang, Hongyuan Zha, Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment SIAM Journal on Scientific Computing. ,vol. 26, pp. 313- 338 ,(2004) , 10.1137/S1064827502419154
Mikhail Belkin, Partha Niyogi, Laplacian Eigenmaps for dimensionality reduction and data representation Neural Computation. ,vol. 15, pp. 1373- 1396 ,(2003) , 10.1162/089976603321780317
A. Hyvärinen, Survey on Independent Component Analysis Neural Computing Surveys. ,vol. 2, pp. 94- 128 ,(1999)
Ian T. Jolliffe, Principal Component Analysis ,(1986)
D.F. Specht, A general regression neural network IEEE Transactions on Neural Networks. ,vol. 2, pp. 568- 576 ,(1991) , 10.1109/72.97934