IPB

Welcome Guest ( Log In | Register )

missing samples
dave1
post Jun 11 2012, 14:25
Post #1





Group: Members
Posts: 4
Joined: 11-June 12
Member No.: 100611



Hi,
I have a question about missing samples, or non-uniform samples. I found out that audio samples can be reconstructed if they are oversampled. My question is can a 20 second oversampled audio file be reconstructed from the first or last 10s of the same recording, or recover a missing audio from what ever that you have. I know that this has something to do with Fourier transform, so, please, can someone explain me how it`s done, or can it be done? I suspect it is possible with simple uniform frequencies, but not with real life audio recordings.
Thanks
Go to the top of the page
+Quote Post
 
Start new topic
Replies
dave1
post Jun 11 2012, 18:40
Post #2





Group: Members
Posts: 4
Joined: 11-June 12
Member No.: 100611



Thank you all, those are great answers. So, when you missing bulk samples, i.e. last tenth or last half, doesn`t matter, it is impossible to recover it, but, as @lvqcl pointed out, if you have every second, or forth, or eight sample (the power of two rule applies here, I assume), the recovery of all samples is possible without loss. It seams that, basicaly, it all comes down to sample resolution. I didn`t see the undersampled option, thanks for pointing it out, @pdq. And, of course, corrupted samples are another matter all together.
Go to the top of the page
+Quote Post
greynol
post Jun 11 2012, 18:57
Post #3





Group: Super Moderator
Posts: 10000
Joined: 1-April 04
From: San Francisco
Member No.: 13167



QUOTE (dave1 @ Jun 11 2012, 10:40) *
the power of two rule applies here, I assume

No, it is only because Ivqcl arbitrarily used an oversampling factor that was a power of two.

If you oversampled by something that isn't so conveniently neat and tidy like 96/44.1 then you can't eliminate all but every x*n sample where n is some power of two (or some other integer that is not a power of two!) and retain the information.

This post has been edited by greynol: Jun 11 2012, 19:17


--------------------
Your eyes cannot hear.
Go to the top of the page
+Quote Post
dave1
post Jun 11 2012, 20:30
Post #4





Group: Members
Posts: 4
Joined: 11-June 12
Member No.: 100611



QUOTE (greynol @ Jun 11 2012, 18:57) *
If you oversampled by something that isn't so conveniently neat and tidy like 96/44.1 then you can't eliminate all but every x*n sample where n is some power of two (or some other integer that is not a power of two!) and retain the information.

Do you talking about prime number (dividable only by itself and 1) as a number of samples here? Because in that case you would be wright, and for every integer there would be a remainder which would represent bulk loss of samples and information. I assumed the power of two because of Fast Fourier Transform algorithm which requires that condition. I believed that every sample reconstruction algorithm uses FFT, but I guess I`m wrong.

I`m also curious about the limit of missing samples. How much samples can you throw away before the recovery of those samples becomes unreliable or incomplete?
Go to the top of the page
+Quote Post

Posts in this topic


Reply to this topicStart new topic
1 User(s) are reading this topic (1 Guests and 0 Anonymous Users)
0 Members:

 



RSS Lo-Fi Version Time is now: 19th April 2014 - 00:18