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I am working in compressed sensing, basically in ECG reconstruction

Normally we were using biorthogonal wavelets for reconstruction.

Someone advised me to use exponential spline basis instead of biorthogonal wavelets and I tried it and the results were better compared to wavelets.

Even though I got better results I still don't know why it worked. I am going for presentation and I am expecting this question.

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  • $\begingroup$ The image-processing tag seems wrong. Care to comment on that? $\endgroup$ Dec 17 '15 at 11:09
  • $\begingroup$ Compressed sensing is mainly done on images ..so I think it matters $\endgroup$
    – Abhishek
    Jan 1 '18 at 12:13
  • $\begingroup$ No, compressed sensing, as far as I know, is a general technique applicable to periodic sampling; invention probably happened first in the audio or rf signal context. $\endgroup$ Jan 2 '18 at 11:01
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That's the old question:

You say it's better, and wonder why, and everyone can only ask you to mathematically define better.

As soon as you define a measure for processing quality, you will be able, typically with not too much linear algebra, derive based on the properties of your signal, your measure and your basis, why one is better than the other.

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