W. Ren, C. Zhang, T. Mu, and H. Dai, “Spectrum reconstruction based on the constrained optimal linear inverse methods,” Opt. Lett.37(13), 2580–2582 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, W. Ren, and C. Jia, “Static polarization-difference interference imaging spectrometer,” Opt. Lett.37(17), 3507–3509 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, C. Jia, and W. Ren, “Static hyperspectral imaging polarimeter for full linear Stokes parameters,” Opt. Express20(16), 18194–18201 (2012).

[CrossRef]
[PubMed]

A. Moghtaderi, P. Borgnat, and P. Flandrin, “Trend filtering: empirical mode decompositions Versus l1 and Hodrick-Prescott,” Adv. Adapt. Data Anal.3, 41–61 (2011).

[CrossRef]

M. Blanco-Velasco, B. Weng, and K. E. Barner, “ECG signal de-noising and baseline wander correction based on the empirical mode decomposition,” Comput. Biol. Med.38(1), 1–13 (2008).

[CrossRef]
[PubMed]

Q. Gao, C. Duan, H. Fan, and Q. Meng, “Rotating machine fault diagnosis using empirical mode decomposition,” Mech. Syst. Signal Process.22(5), 1072–1081 (2008).

[CrossRef]

Q. Kemao, “A simple phase unwrapping approach based on filtering by windowed Fourier transform: a note on the threshold selection,” Opt. Laser Technol.40(8), 1091–1098 (2008).

[CrossRef]

L. Wu, C. Zhang, and B. Zhao, “Analysis of the lateral displacement and optical path difference in Wide-field-of –view polarization interference imaging spectrometer,” Opt. Commun.273(1), 67–73 (2007).

[CrossRef]

P. D. Spanos, A. Giaralis, and N. P. Politis, “Time-frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition,” Soil. Dyn. Earthquake Eng.27(7), 675–689 (2007).

[CrossRef]

A. O. Boudraa and J. C. Cexus, “EMD-based signal filtering,” IEEE Trans. Instrum. Meas.56(6), 2196–2202 (2007).

[CrossRef]

H. Liang, Q. H. Lin, and J. D. Z. Chen, “Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease,” IEEE Trans. Biomed. Eng.52(10), 1692–1701 (2005).

[CrossRef]
[PubMed]

P. Flandrin, G. Rilling, and P. Gonçalves, “Empirical mode decomposition as a filter bank,” IEEE Signal Process. Lett.11(2), 112–114 (2004).

[CrossRef]

Z. Wu and N. E. Huang, “A study of the characteristcs of white noise using the Empirical Mode Decomposition method,” Proc. R. Soc. Lond. A460(2046), 1597–1611 (2004).

[CrossRef]

A. O. Boudraa, J. C. Cexus, and Z. Saidi, “EMD-based signal noise reduction,” Int. J. Signal Process.1, 33–37 (2004).

H. Liang, Z. Lin, and R. W. McCallum, “Artifact reduction in electrogastrogram based on empirical mode decomposition method,” Med. Biol. Eng. Comput.38(1), 35–41 (2000).

[CrossRef]
[PubMed]

C. Zhang, X. Bin, and B. Zhao, “Static polarization interference imaging spectrometer (SPIIS),” Proc. SPIE4087, 957–961 (2000).

[CrossRef]

N. E. Huang, Z. Shen, and S. R. Long, “A new view of nonlinear water waves: The Hilbert spectrum,” Annu. Rev. Fluid Mech.31(1), 417–457 (1999).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

L. Donoho, “De-noising by soft-thresholding,” IEEE Trans. Inf. Theory41(3), 613–627 (1995).

[CrossRef]

M. Blanco-Velasco, B. Weng, and K. E. Barner, “ECG signal de-noising and baseline wander correction based on the empirical mode decomposition,” Comput. Biol. Med.38(1), 1–13 (2008).

[CrossRef]
[PubMed]

C. Zhang, X. Bin, and B. Zhao, “Static polarization interference imaging spectrometer (SPIIS),” Proc. SPIE4087, 957–961 (2000).

[CrossRef]

M. Blanco-Velasco, B. Weng, and K. E. Barner, “ECG signal de-noising and baseline wander correction based on the empirical mode decomposition,” Comput. Biol. Med.38(1), 1–13 (2008).

[CrossRef]
[PubMed]

A. Moghtaderi, P. Borgnat, and P. Flandrin, “Trend filtering: empirical mode decompositions Versus l1 and Hodrick-Prescott,” Adv. Adapt. Data Anal.3, 41–61 (2011).

[CrossRef]

A. O. Boudraa and J. C. Cexus, “EMD-based signal filtering,” IEEE Trans. Instrum. Meas.56(6), 2196–2202 (2007).

[CrossRef]

A. O. Boudraa, J. C. Cexus, and Z. Saidi, “EMD-based signal noise reduction,” Int. J. Signal Process.1, 33–37 (2004).

A. O. Boudraa and J. C. Cexus, “EMD-based signal filtering,” IEEE Trans. Instrum. Meas.56(6), 2196–2202 (2007).

[CrossRef]

A. O. Boudraa, J. C. Cexus, and Z. Saidi, “EMD-based signal noise reduction,” Int. J. Signal Process.1, 33–37 (2004).

H. Liang, Q. H. Lin, and J. D. Z. Chen, “Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease,” IEEE Trans. Biomed. Eng.52(10), 1692–1701 (2005).

[CrossRef]
[PubMed]

L. Donoho, “De-noising by soft-thresholding,” IEEE Trans. Inf. Theory41(3), 613–627 (1995).

[CrossRef]

Q. Gao, C. Duan, H. Fan, and Q. Meng, “Rotating machine fault diagnosis using empirical mode decomposition,” Mech. Syst. Signal Process.22(5), 1072–1081 (2008).

[CrossRef]

Q. Gao, C. Duan, H. Fan, and Q. Meng, “Rotating machine fault diagnosis using empirical mode decomposition,” Mech. Syst. Signal Process.22(5), 1072–1081 (2008).

[CrossRef]

A. Moghtaderi, P. Borgnat, and P. Flandrin, “Trend filtering: empirical mode decompositions Versus l1 and Hodrick-Prescott,” Adv. Adapt. Data Anal.3, 41–61 (2011).

[CrossRef]

P. Flandrin, G. Rilling, and P. Gonçalves, “Empirical mode decomposition as a filter bank,” IEEE Signal Process. Lett.11(2), 112–114 (2004).

[CrossRef]

Q. Gao, C. Duan, H. Fan, and Q. Meng, “Rotating machine fault diagnosis using empirical mode decomposition,” Mech. Syst. Signal Process.22(5), 1072–1081 (2008).

[CrossRef]

P. D. Spanos, A. Giaralis, and N. P. Politis, “Time-frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition,” Soil. Dyn. Earthquake Eng.27(7), 675–689 (2007).

[CrossRef]

P. Flandrin, G. Rilling, and P. Gonçalves, “Empirical mode decomposition as a filter bank,” IEEE Signal Process. Lett.11(2), 112–114 (2004).

[CrossRef]

Z. Wu and N. E. Huang, “A study of the characteristcs of white noise using the Empirical Mode Decomposition method,” Proc. R. Soc. Lond. A460(2046), 1597–1611 (2004).

[CrossRef]

N. E. Huang, Z. Shen, and S. R. Long, “A new view of nonlinear water waves: The Hilbert spectrum,” Annu. Rev. Fluid Mech.31(1), 417–457 (1999).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

T. Mu, C. Zhang, W. Ren, and C. Jia, “Static polarization-difference interference imaging spectrometer,” Opt. Lett.37(17), 3507–3509 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, C. Jia, and W. Ren, “Static hyperspectral imaging polarimeter for full linear Stokes parameters,” Opt. Express20(16), 18194–18201 (2012).

[CrossRef]
[PubMed]

Q. Kemao, “A simple phase unwrapping approach based on filtering by windowed Fourier transform: a note on the threshold selection,” Opt. Laser Technol.40(8), 1091–1098 (2008).

[CrossRef]

H. Liang, Q. H. Lin, and J. D. Z. Chen, “Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease,” IEEE Trans. Biomed. Eng.52(10), 1692–1701 (2005).

[CrossRef]
[PubMed]

H. Liang, Z. Lin, and R. W. McCallum, “Artifact reduction in electrogastrogram based on empirical mode decomposition method,” Med. Biol. Eng. Comput.38(1), 35–41 (2000).

[CrossRef]
[PubMed]

H. Liang, Q. H. Lin, and J. D. Z. Chen, “Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease,” IEEE Trans. Biomed. Eng.52(10), 1692–1701 (2005).

[CrossRef]
[PubMed]

H. Liang, Z. Lin, and R. W. McCallum, “Artifact reduction in electrogastrogram based on empirical mode decomposition method,” Med. Biol. Eng. Comput.38(1), 35–41 (2000).

[CrossRef]
[PubMed]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

N. E. Huang, Z. Shen, and S. R. Long, “A new view of nonlinear water waves: The Hilbert spectrum,” Annu. Rev. Fluid Mech.31(1), 417–457 (1999).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

H. Liang, Z. Lin, and R. W. McCallum, “Artifact reduction in electrogastrogram based on empirical mode decomposition method,” Med. Biol. Eng. Comput.38(1), 35–41 (2000).

[CrossRef]
[PubMed]

Q. Gao, C. Duan, H. Fan, and Q. Meng, “Rotating machine fault diagnosis using empirical mode decomposition,” Mech. Syst. Signal Process.22(5), 1072–1081 (2008).

[CrossRef]

A. Moghtaderi, P. Borgnat, and P. Flandrin, “Trend filtering: empirical mode decompositions Versus l1 and Hodrick-Prescott,” Adv. Adapt. Data Anal.3, 41–61 (2011).

[CrossRef]

T. Mu, C. Zhang, C. Jia, and W. Ren, “Static hyperspectral imaging polarimeter for full linear Stokes parameters,” Opt. Express20(16), 18194–18201 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, W. Ren, and C. Jia, “Static polarization-difference interference imaging spectrometer,” Opt. Lett.37(17), 3507–3509 (2012).

[CrossRef]
[PubMed]

W. Ren, C. Zhang, T. Mu, and H. Dai, “Spectrum reconstruction based on the constrained optimal linear inverse methods,” Opt. Lett.37(13), 2580–2582 (2012).

[CrossRef]
[PubMed]

P. D. Spanos, A. Giaralis, and N. P. Politis, “Time-frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition,” Soil. Dyn. Earthquake Eng.27(7), 675–689 (2007).

[CrossRef]

T. Mu, C. Zhang, W. Ren, and C. Jia, “Static polarization-difference interference imaging spectrometer,” Opt. Lett.37(17), 3507–3509 (2012).

[CrossRef]
[PubMed]

W. Ren, C. Zhang, T. Mu, and H. Dai, “Spectrum reconstruction based on the constrained optimal linear inverse methods,” Opt. Lett.37(13), 2580–2582 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, C. Jia, and W. Ren, “Static hyperspectral imaging polarimeter for full linear Stokes parameters,” Opt. Express20(16), 18194–18201 (2012).

[CrossRef]
[PubMed]

P. Flandrin, G. Rilling, and P. Gonçalves, “Empirical mode decomposition as a filter bank,” IEEE Signal Process. Lett.11(2), 112–114 (2004).

[CrossRef]

A. O. Boudraa, J. C. Cexus, and Z. Saidi, “EMD-based signal noise reduction,” Int. J. Signal Process.1, 33–37 (2004).

N. E. Huang, Z. Shen, and S. R. Long, “A new view of nonlinear water waves: The Hilbert spectrum,” Annu. Rev. Fluid Mech.31(1), 417–457 (1999).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

P. D. Spanos, A. Giaralis, and N. P. Politis, “Time-frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition,” Soil. Dyn. Earthquake Eng.27(7), 675–689 (2007).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

M. Blanco-Velasco, B. Weng, and K. E. Barner, “ECG signal de-noising and baseline wander correction based on the empirical mode decomposition,” Comput. Biol. Med.38(1), 1–13 (2008).

[CrossRef]
[PubMed]

L. Wu, C. Zhang, and B. Zhao, “Analysis of the lateral displacement and optical path difference in Wide-field-of –view polarization interference imaging spectrometer,” Opt. Commun.273(1), 67–73 (2007).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

Z. Wu and N. E. Huang, “A study of the characteristcs of white noise using the Empirical Mode Decomposition method,” Proc. R. Soc. Lond. A460(2046), 1597–1611 (2004).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

T. Mu, C. Zhang, C. Jia, and W. Ren, “Static hyperspectral imaging polarimeter for full linear Stokes parameters,” Opt. Express20(16), 18194–18201 (2012).

[CrossRef]
[PubMed]

W. Ren, C. Zhang, T. Mu, and H. Dai, “Spectrum reconstruction based on the constrained optimal linear inverse methods,” Opt. Lett.37(13), 2580–2582 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, W. Ren, and C. Jia, “Static polarization-difference interference imaging spectrometer,” Opt. Lett.37(17), 3507–3509 (2012).

[CrossRef]
[PubMed]

C. Zhang and X. Jian, “Wide-spectrum reconstruction method for a birefringence interference imaging spectrometer,” Opt. Lett.35(3), 366–368 (2010).

[CrossRef]
[PubMed]

X. Jian, C. Zhang, L. Zhang, and B. Zhao, “The data processing of the temporarily and spatially mixed modulated polarization interference imaging spectrometer,” Opt. Express18(6), 5674–5680 (2010).

[CrossRef]
[PubMed]

L. Wu, C. Zhang, and B. Zhao, “Analysis of the lateral displacement and optical path difference in Wide-field-of –view polarization interference imaging spectrometer,” Opt. Commun.273(1), 67–73 (2007).

[CrossRef]

C. Zhang, X. Bin, and B. Zhao, “Static polarization interference imaging spectrometer (SPIIS),” Proc. SPIE4087, 957–961 (2000).

[CrossRef]

X. Jian, C. Zhang, L. Zhang, and B. Zhao, “The data processing of the temporarily and spatially mixed modulated polarization interference imaging spectrometer,” Opt. Express18(6), 5674–5680 (2010).

[CrossRef]
[PubMed]

L. Wu, C. Zhang, and B. Zhao, “Analysis of the lateral displacement and optical path difference in Wide-field-of –view polarization interference imaging spectrometer,” Opt. Commun.273(1), 67–73 (2007).

[CrossRef]

C. Zhang, X. Bin, and B. Zhao, “Static polarization interference imaging spectrometer (SPIIS),” Proc. SPIE4087, 957–961 (2000).

[CrossRef]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

A. Moghtaderi, P. Borgnat, and P. Flandrin, “Trend filtering: empirical mode decompositions Versus l1 and Hodrick-Prescott,” Adv. Adapt. Data Anal.3, 41–61 (2011).

[CrossRef]

N. E. Huang, Z. Shen, and S. R. Long, “A new view of nonlinear water waves: The Hilbert spectrum,” Annu. Rev. Fluid Mech.31(1), 417–457 (1999).

[CrossRef]

M. Blanco-Velasco, B. Weng, and K. E. Barner, “ECG signal de-noising and baseline wander correction based on the empirical mode decomposition,” Comput. Biol. Med.38(1), 1–13 (2008).

[CrossRef]
[PubMed]

P. Flandrin, G. Rilling, and P. Gonçalves, “Empirical mode decomposition as a filter bank,” IEEE Signal Process. Lett.11(2), 112–114 (2004).

[CrossRef]

H. Liang, Q. H. Lin, and J. D. Z. Chen, “Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease,” IEEE Trans. Biomed. Eng.52(10), 1692–1701 (2005).

[CrossRef]
[PubMed]

L. Donoho, “De-noising by soft-thresholding,” IEEE Trans. Inf. Theory41(3), 613–627 (1995).

[CrossRef]

A. O. Boudraa and J. C. Cexus, “EMD-based signal filtering,” IEEE Trans. Instrum. Meas.56(6), 2196–2202 (2007).

[CrossRef]

A. O. Boudraa, J. C. Cexus, and Z. Saidi, “EMD-based signal noise reduction,” Int. J. Signal Process.1, 33–37 (2004).

Q. Gao, C. Duan, H. Fan, and Q. Meng, “Rotating machine fault diagnosis using empirical mode decomposition,” Mech. Syst. Signal Process.22(5), 1072–1081 (2008).

[CrossRef]

H. Liang, Z. Lin, and R. W. McCallum, “Artifact reduction in electrogastrogram based on empirical mode decomposition method,” Med. Biol. Eng. Comput.38(1), 35–41 (2000).

[CrossRef]
[PubMed]

L. Wu, C. Zhang, and B. Zhao, “Analysis of the lateral displacement and optical path difference in Wide-field-of –view polarization interference imaging spectrometer,” Opt. Commun.273(1), 67–73 (2007).

[CrossRef]

X. Jian, C. Zhang, L. Zhang, and B. Zhao, “The data processing of the temporarily and spatially mixed modulated polarization interference imaging spectrometer,” Opt. Express18(6), 5674–5680 (2010).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, C. Jia, and W. Ren, “Static hyperspectral imaging polarimeter for full linear Stokes parameters,” Opt. Express20(16), 18194–18201 (2012).

[CrossRef]
[PubMed]

Q. Kemao, “A simple phase unwrapping approach based on filtering by windowed Fourier transform: a note on the threshold selection,” Opt. Laser Technol.40(8), 1091–1098 (2008).

[CrossRef]

C. Zhang and X. Jian, “Wide-spectrum reconstruction method for a birefringence interference imaging spectrometer,” Opt. Lett.35(3), 366–368 (2010).

[CrossRef]
[PubMed]

W. Ren, C. Zhang, T. Mu, and H. Dai, “Spectrum reconstruction based on the constrained optimal linear inverse methods,” Opt. Lett.37(13), 2580–2582 (2012).

[CrossRef]
[PubMed]

T. Mu, C. Zhang, W. Ren, and C. Jia, “Static polarization-difference interference imaging spectrometer,” Opt. Lett.37(17), 3507–3509 (2012).

[CrossRef]
[PubMed]

N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A454(1971), 903–995 (1998).

[CrossRef]

Z. Wu and N. E. Huang, “A study of the characteristcs of white noise using the Empirical Mode Decomposition method,” Proc. R. Soc. Lond. A460(2046), 1597–1611 (2004).

[CrossRef]

C. Zhang, X. Bin, and B. Zhao, “Static polarization interference imaging spectrometer (SPIIS),” Proc. SPIE4087, 957–961 (2000).

[CrossRef]

P. D. Spanos, A. Giaralis, and N. P. Politis, “Time-frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition,” Soil. Dyn. Earthquake Eng.27(7), 675–689 (2007).

[CrossRef]

R. J. Bell, Introductory Fourier Transform Spectroscopy (Academic Press & London, 1972), Chap. 3.