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3:58 AM
A new tag was created by NicNic8.
Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined linear systems. This is based on the principle that, through optimization, the sparsity of a signal can be exploited to recover it from far fewer samples than required by the Nyquist–Shannon sampling theorem. There are two conditions under which recovery is possible. The first one is sparsity, which requires the signal to be sparse in some domain. The second one is incoherence...
 
 
1 hour later…
5:21 AM
As the questions is likely to be autodeleted, perhaps it makes sense to save this comment here:
It seems to me that a "geometry without trigonometry" tag is likely not to be all that useful---it has been a while, but my recollection is that I didn't even know that trigonometry was a thing until after I started learning it---someone who does not know what a sine or cosine is may also be unaware of the entire field of trigonometry, and may not know to use such a tag. Instead, I think that this a very good example of why we ask users to provide context. Had the asker explained the kind of class that they are taking, it is quite likely that folk would have known how to answer. — Xander Henderson 15 hours ago
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