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The multidimensional harmonic retrieval problem is an important topic which arises in several applications [1].
More specifically, the retrieval problem is focused on the estimation of the fault parameters from the InSAR differential interferogram.
The phase retrieval problem is made tractable in ptychography by recording multiple diffraction patterns from overlapping regions of the object, providing redundant datasets to compensate for the lack of the phase information.
The information retrieval problem is to find the right document, or documents, that will help satisfy a searcher's information need.
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The classification problem as well as the retrieval problem was satisfactorily managed with both the pre-processing stages.
No retrieval problems were identified, this may be due to none of the items asking participants to recall details of frequency of events, but also suggests that asking the participants to recall their experiences over the past four weeks was an achievable task.
When the sinusoids are sparse, i.e., K << M, harmonic retrieval problem can be solved by grid-based CS approaches.
In Section 4, we see how the 1-D modal retrieval problem may be addressed using sparse approximations and how the multigrid approach can be applied.
(ii) We show how the 1-D modal retrieval problem can be addressed using sparse estimation approach by building a dictionary whose atoms are calculated by sampling the modal function over a 2-D grid (frequency and damping factor) in order to obtain all possible modes combinations.
Then the R-D modal retrieval problem can be formulated as a penalized ℓ2 - ℓ0 sparse signal estimation problem (2).
Similar to the 1-D case, the R-D modal retrieval problem can be formulated as a sparse signal estimation problem by defining a dictionary that gathers all possible combinations of 1-D modes obtained by sampling damping factors and frequencies for each dimension on 2-D grids.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com