January 2019
Intermediate to advanced
294 pages
6h 43m
English
Content preview from Machine Learning Quick Reference
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Our goal
Our goal is to find out the solution with a least possible non-zero entry of all of the solutions. That is, the solution should give us as few non-zeros as possible. Are you wondering where this can be applied? There are plenty of applications for it. The areas where it can be applied are as follows:
- Signal representation
- Medical imaging
- Sparse channel estimation
Let's say that we have got a time signal. This signal is highly sparse, but we know a little bit about it as it has a few frequencies. Can you sense what it is from the earlier equation? Yes, it can be deemed as X.
Let's call this unknown signal X. Now, even though we don't know the whole signal, we can still make observations about it, or samples, as shown in the following ...
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