Timeline for Compressed sensing / compressive sensing: what is the lower bound on dimension of the measurement matrix?
Current License: CC BY-SA 4.0
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| Nov 20, 2022 at 3:36 | history | edited | Zebra Fish | CC BY-SA 4.0 |
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| Nov 20, 2022 at 0:56 | comment | added | Zebra Fish | Thank you @Dustin, I will take a look at Foucart and Rauhut | |
| Nov 19, 2022 at 23:10 | comment | added | Dustin G. Mixon | The bound depends on what you mean by "full recovery". The restriction of $x\mapsto Mx$ to the set of $k$-sparse vectors is injective only if $m\geq 2k$, in which case one can theoretically recover $x$ from $Mx$, but the algorithm might be slow. Meanwhile, a computationally efficient algorithm like $\ell_1$ minimization requires $m=\Omega(k\log(n/k))$. Foucart and Rauhut's book is the go-to reference for these things. | |
| Nov 19, 2022 at 18:55 | history | edited | Zebra Fish | CC BY-SA 4.0 |
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| Nov 19, 2022 at 17:49 | history | edited | Zebra Fish | CC BY-SA 4.0 |
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| Nov 19, 2022 at 16:32 | history | edited | Zebra Fish | CC BY-SA 4.0 |
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| S Nov 19, 2022 at 16:28 | review | First questions | |||
| Nov 19, 2022 at 17:48 | |||||
| S Nov 19, 2022 at 16:28 | history | asked | Zebra Fish | CC BY-SA 4.0 |