Bandwidth empirical mode decomposition and its application

International Journal of Wavelets, Multiresolution and Information Processing

Volumn 6, Issue 6, 2008, Pages 777-798

  Xie, Qiwei ^a,b   Xuan, Bo ^c   Peng, Silong ^c   Li, Jianping ^b   Xu, Weixuan ^b   Han, Hua ^c  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b Chinese Academy of Sciences   (China)

^c INSTITUTE OF AUTOMATION   (China)

Author keywords

Empirical Mode Decomposition (EMD); Instantaneous frequency; Intrinsic Mode Function (IMF); Sifting algorithm

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; ADAPTIVE ALGORITHMS; BANDWIDTH; ELECTRIC LOAD FORECASTING; ELECTRIC POWER UTILIZATION; PROBABILITY DENSITY FUNCTION; SIGNAL ANALYSIS; TELECOMMUNICATION SYSTEMS; WAVELET DECOMPOSITION; WAVELET TRANSFORMS;

CONVERGENCE PROPERTIES; ELECTRICITY CONSUMPTIONS; EMPIRICAL MODE DECOMPOSITION (EMD); EMPIRICAL MODE DECOMPOSITIONS; FOURIER DECOMPOSITIONS; INSTANTANEOUS FREQUENCY; INTRINSIC MODE FUNCTION (IMF); INTRINSIC MODE FUNCTIONS; MULTISCALE ANALYSES; NONSTATIONARY SIGNALS; POWERFUL TOOLS; REAL COMPONENTS; SIFTING ALGORITHM; SIGNAL DECOMPOSITIONS; TIME SERIES DECOMPOSITIONS;

SIGNAL PROCESSING;

EID: 56349130292     PISSN: 02196913     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219691308002689     Document Type: Article

References (22)

1. N. E. Huang et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. Roy. Soc. Lond. Ser. A. 454 (1998) 903-995.
2. N. E. Huang, Z. Shen and S. R. Long, A new view of nonlinear water waves: The Hilbert Spectrum, Ann. Rev. Fluid Mech. 31 (1999) 417-457.
3. Y. L. Xu, M. Asce and J. Chen, Structural damage detection using empirical mode decomposition: Experimental investigation, J. Eng. Mech. 130(11) (2004) 1279-1288.
4. Z. Liu and S. Peng, Boundary processing of bidimensional EMD using texture synthesis, IEEE Signal Process. Lett. 12 (2005) 33-36.
5. C. De Boor, A Practical Guide to Splines (Springer-Verlag, 2001).
6. P. Flandrin, G. Rilling and P. Goncalves, Empirical mode decomposition as a filter bank, IEEE Signal Process. Lett. 11(2) (2004) 112-114.
7. C. Damerval, S. Meignen and V. Perrier, A fast algorithm for bidimensional EMD, IEEE Signal Process. Lett. 12(10) (2005) 123-125.
8. J. S. Cheng et al., Research on the intrinsic mode function (IMF) criterion in EMD method, Mech. Syst. Signal Process. 20 (2006) 817-824.
9. H. G. Li and G. Meng, Detection of harmonic signals from chaotic interference by empirical mode decomposition, Chaos Solitons Fractals 30(4) (2006) 930-935.
10. B. Shen, Estimating the instantaneous frequencies of a multicomponent AM-FM image by bidimensional empirical mode decomposition, in Proc. IEEE Int. Workshop on Intelligent Signal Processing (WISP'05), Faro, Portugal (2005), pp. 283-287.
11. G. Rilling, P. Flandrin and P. Goncalves, On empirical mode decomposition and its algorithms, in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP'03), Grado, Italy (2003), 5 pp; http://perso.ens-lyon.fr/paulo.goncalves/pub/emd-eurasip03.pdf.
12. P. Loughlin and B. Tacer, Comments on the interpretation of instantaneous frequency, IEEE Signal Process. Lett. 4 (1997) 123-125.
13. D. Wei and A. C. Bovik, On the Instantaneous frequencies of multicomponent AM-FM signals, IEEE Signal Process. Lett. 45 (1997) 867-869.
14. L. Cohen, Time-Frequency Analysis (Prentice-Hall, NJ, 1995).
15. B. Boashash, Estimating and interpreting the instantaneous frequency of a signal, Proc. IEEE. 80(4) (1992) 519-569.
16. B. Xuan, Q. Xie and S. Peng, EMD sifting based on bandwidth, IEEE Signal Process. Lett. 14(8) (2007) 537-540.
17. Q. Xie and B. Xuan, EMD algorithm based on bandwidth and the application on one economic data analysis, in Proc. European Signal Processing Conference, Poznań, Poland (2007), pp. 2419-2423.
18. G. Simon, A. Lendasse and M. Cottrell, Time series forecasting: Obtaining long term trends with self-organizing maps, Pattern Recogn. Lett. 26 (2005) 1795-1808.
19. A. Lendasse, P. Cardon and V. Wertz, Forecasting electricity consumption using nonlinear projection and self-organizing maps, Neurocomputing 48 (2002) 299-311.
20. M. Baxter and R. G. King, Measuring business cycles: Approximate band-pass filters for economic time series, Rev. Econ. Stat. 81 4) (1999) 575-593.
21. A. C. Harvey and T. Trimbur, General model-based filters for extracting cycles and trends in economic time series, Rev. Econ. Stat. 85 2) (2003) 244-255.
22. D. S. G. Pollock, Methodology for trend estimation, Econ. Mod. 18(1) (2001) 75-96.