Difference between revisions of "Hilbert-Huang Transform"

From Jeskola Buzz Wiki
Jump to: navigation, search
m (How to do it (in plain english))
Line 11: Line 11:
 
# Overwrite the original signal with the new "mean curve" and jump back to 1. Repeat this 4 to 8 times ([http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.92.1156&rep=rep1&type=pdf According to Professor Huang.])
 
# Overwrite the original signal with the new "mean curve" and jump back to 1. Repeat this 4 to 8 times ([http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.92.1156&rep=rep1&type=pdf According to Professor Huang.])
 
# Do a Hilbert transform on all the resulting outputs from step 5.
 
# Do a Hilbert transform on all the resulting outputs from step 5.
 +
 +
[Category:Design propositions]
 +
[Category:Development]

Revision as of 22:50, 23 November 2010

Hilbert space

Trying to decipher a rather nerdy and way too math heavy pdf - this might not be correct, but here goes nothing...

How to do it (in plain english)

  1. Start by finding all local peaks and valleys of the audio data. The trick is: Everytime you see a sample that is taller than both the next and the previous sample, it's a peak. Everytime you see a sample that is lower than both the next and the previous sample, it's a valley.
  2. Do a "nice" interpolation between all the peaks. Let's call this the "max curve".
  3. Do a "nice" interpolation between all the valleys. Let's call this the "min curve".
  4. Create a resulting "mean curve" by averaging min and max: mean = (min+max)/2
  5. Save the difference between the original signal and the new "mean curve" as the first (or second or third) iteration.
  6. Overwrite the original signal with the new "mean curve" and jump back to 1. Repeat this 4 to 8 times (According to Professor Huang.)
  7. Do a Hilbert transform on all the resulting outputs from step 5.

[Category:Design propositions] [Category:Development]