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Solving End-point problem

Solving End-point problem. Method. DMP have more serious end-point problem then EEMD Test extraction should be performed to ensure the behavior of DMP and EEMD modes Observe the range of EEMD that may combine with DMP Adjust COMB(6) and COMB(7) to the desired range

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Solving End-point problem

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  1. Solving End-point problem

  2. Method • DMP have more serious end-point problem then EEMD • Test extraction should be performed to ensure the behavior of DMP and EEMD modes • Observe the range of EEMD that may combine with DMP • Adjust COMB(6) and COMB(7) to the desired range • Observe whether the end-point problem is serious

  3. Cont. • In case it is serious, we need to adjust 3 set of EJME parameters: • Critical Amplitude(COMB(5)) and • Critical correlation(COMB(4)) • The plateau function(COMB(2)) (COMB(3))

  4. How to set those parameters • Open ejme.m • Increase COMB(2) and decrease COMB(3) • compress the domain of plateau function • Decrease COMB(4) and COMB(5) to enhance combination • Alter COMB(6) and COMB(7) according to trial eemd • Note that COMB(2)-(5) should not be varied too much

  5. Demonstration(L:original,R:Modified)

  6. An Intuitive example

  7. Full Example • Noised time series that has • a trend term, • two sinusoidal components • a white noise term

  8. FFT Spectrum • 2 peaks • We extract f=1.5 first

  9. End-Point Problem • End point problem is a nuisance at the right end • DMP has 1 less peak than expected

  10. 2nd Extraction • Pick f=3.5

  11. End point problem • For this mode end-point problem is even more rampant. • Phase is slightly distorted

  12. EEMD modes

  13. p Target EEMD modes

  14. An Intuitive example(Revisited)

  15. EJME Result

  16. Comparison • IMF3 looks a lot better • slight improvement on IMF2 • This demonstrates how to save DMP from end-point problem

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