dc.contributor.advisor | Narayanan, Krishna | |
dc.creator | Gao, Jiahui | |
dc.date.accessioned | 2021-04-27T21:23:38Z | |
dc.date.available | 2021-04-27T21:23:38Z | |
dc.date.created | 2020-12 | |
dc.date.issued | 2020-11-20 | |
dc.date.submitted | December 2020 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/192751 | |
dc.description.abstract | We study two problems related to sparse signal recovery.
The first problem considered is querying a sub-image of size square of M in a large image database of size square of N to determine all the locations where sub-image appears. We use sparse graph based codes Fourier transform computation to compute the peaks in the 2-D correlation to determine the matching positions in a computationally efficient manner.
We then design a 2-D pattern that can facilitate vision based positioning by enabling the use of our algorithm for fast pattern matching. The second problem studied is the computation of sparse Walsh-Hadamard transform for binary data. We consider signals that are sparse in Walsh-Hadamard tranform domain where the non-zero coefficients are all ones. A possible application of this algorithm is learning an undirected unweighted graph by using a sub-sample version of its evaluation. We design an adaptive algorithm for sparse WHT computation. Adaptivity provides an opportunity to recover more than one non-zero coefficient aliased together in each iteration so that a faster recovery can be expected given the same amount of sub-samples. It is shown that with the same amount sample, the probability of error of our proposed algorithm is lower compared to the earlier work. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.subject | Sparse signal recovery | en |
dc.subject | 2-D pattern matching | en |
dc.subject | Sparse Walsh-Hadamard Transform computation | en |
dc.title | Applications of Sparse Signal Recovery: 2D-Pattern Matching and Sparse Walsh-Hadamard Transform Computation | en |
dc.type | Thesis | en |
thesis.degree.department | Electrical and Computer Engineering | en |
thesis.degree.discipline | Electrical Engineering | en |
thesis.degree.grantor | Texas A&M University | en |
thesis.degree.name | Master of Science | en |
thesis.degree.level | Masters | en |
dc.contributor.committeeMember | Jiang, Anxiao | |
dc.contributor.committeeMember | Chamberland, Jean-Francois | |
dc.contributor.committeeMember | Duffield, Nick | |
dc.type.material | text | en |
dc.date.updated | 2021-04-27T21:23:39Z | |
local.etdauthor.orcid | 0000-0003-3821-2263 | |