Please wait a minute...
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2001, Vol. 2 Issue (3): 247-252    DOI: 10.1631/jzus.2001.0247
Science & Engineering     
MIRROR EXTENDING AND CIRCULAR SPLINE FUNCTION FOR EMPIRICAL MODE DECOMPOSITION METHOD
ZHAO Jin-ping, HUANG Da-ji
Second Institute of Oceanography, State Oceanic Administration, Hangzhou, 310012, China
Download:     PDF (0 KB)     
Export: BibTeX | EndNote (RIS)      

Abstract  The Mirror Extending (ME) approach is proposed in this paper for solving the end extending issue in the Empirical Mode Decomposition (EMD) method. By this approach, the data is extended into a closed circuit without end. The derivatives on ends are not necessary any more for Spline fitting. The approach eliminates the possible problems in reliability and uniqueness in the original extending approach of the EMD method. In the ME approach only one extending is necessary before the data analysis. A theoretical criterion is proposed here for checking the extending approach. ME approach has been proved to satisfy the theoretical criterion automatically and permanently. This approach makes the EMD method reliable and easy to follow.

Key wordsempirical mode decomposition      mirror extension      circular Spline function      time series analysis      time-frequency domain     
Received: 14 March 2001     
CLC:  O212.4  
Cite this article:

ZHAO Jin-ping, HUANG Da-ji. MIRROR EXTENDING AND CIRCULAR SPLINE FUNCTION FOR EMPIRICAL MODE DECOMPOSITION METHOD. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2001, 2(3): 247-252.

URL:

http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2001.0247     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2001/V2/I3/247

[1] Yun-luo Yu, Wei Li, De-ren Sheng, Jian-hong Chen. A hybrid short-term load forecasting method based on improved ensemble empirical mode decomposition and back propagation neural network[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(2): 101-114.
[2] Wen-yang Duan, Li-min Huang, Yang Han, De-tai Huang. A hybrid EMD-AR model for nonlinear and non-stationary wave forecasting[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(2): 115-129.
[3] Wen-yang Duan, Li-min Huang, Yang Han, Ya-hui Zhang, Shuo Huang. A hybrid AR-EMD-SVR model for the short-term prediction of nonlinear and non-stationary ship motion[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(7): 562-576.
[4] Arturo Garcia-Perez, Juan P. Amezquita-Sanchez, Aurelio Dominguez-Gonzalez, Ramin Sedaghati, Roque Osornio-Rios, Rene J. Romero-Troncoso. Fused empirical mode decomposition and wavelets for locating combined damage in a truss-type structure through vibration analysis[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2013, 14(9): 615-630.
[5] Qi ZHANG, Pei-wen QUE, Wei LIANG. Applying sub-band energy extraction to noise cancellation of ultrasonic NDT signal[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2008, 9(8): 1134-1140.
[6] Jia-qiang YANG, Jin HUANG, Tong LIU. Diagnosis of stator faults in induction motor based on zero sequence voltage after switch-off[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2008, 9(2): 165-172.
[7] YAN Zhi-guo, WANG Zhi-zhong, REN Xiao-mei. Joint application of feature extraction based on EMD-AR strategy and multi-class classifier based on LS-SVM in EMG motion classification[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2007, 8(8): 1246-1255.
[8] XIONG Chang-zhen, XU Jun-yi, ZOU Jian-cheng, QI Dong-xu. Texture classification based on EMD and FFT[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(9): 1516-1521.
[9] Mao Yi-mei, Que Pei-wen. Application of Hilbert-Huang signal processing to ultrasonic non-destructive testing of oil pipelines[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(2): 130-134.