Advanced Methods for Efficient Digital Signal Processing and Matrix-Based Computations

Simple item page
dc.contributor.advisorDimitrov, Vassil S.
dc.contributor.authorGomes Coelho, Diego Felipe
dc.contributor.committeememberBehjat, Laleh
dc.contributor.committeememberWalus, Konrad
dc.contributor.committeememberYanushkevich, Svetlana N.
dc.contributor.committeememberJacobson, Michael J.
dc.date2018-06
dc.date.accessioned2018-04-17T14:29:04Z
dc.date.available2018-04-17T14:29:04Z
dc.date.issued2018-04-12
dc.description.abstractModern engineering and scientific problems demand a great amount of data processing power. The type of data that needs to be processed varies from application to application. Image processing, genome matching, physics phenomena simulation, and cryptography are a few examples of processing-power demanding applications. In a wide range of those computationally intensive applications, the arithmetic complexity plays an important role, having direct impact on the implementation performance. In this thesis, we present several methods that are novel contributions of the author to some computationally intensive problems. The introduced methods reduce the overall computing time or other relevant hardware’ and software implementation metrics by decreasing the arithmetic complexity associated with each task. Verified results are shown with peer-reviewed journal papers in reputable journals. In particular, problems on signal processing, eigenvalue computation, and matrix inversion for radar image classification are considered.en_US
dc.identifier.citationCoelho, D. F. G. (2018). Advanced Methods for Efficient Digital Signal Processing and Matrix-Based Computations (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/31793en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/31793
dc.identifier.urihttp://hdl.handle.net/1880/106505
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.facultySchulich School of Engineering
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectFast Algorithms
dc.subjectDigital Signal Processing
dc.subjectMatrix Computation
dc.subject.classificationEngineering--Electronics and Electricalen_US
dc.titleAdvanced Methods for Efficient Digital Signal Processing and Matrix-Based Computations
dc.typedoctoral thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
ucalgary.thesis.checklistI confirm that I have submitted all of the required forms to Faculty of Graduate Studies.en_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ucalgary_2018_gomescoelho_diegofelipe.pdf
Size:
3.34 MB
Format:
Adobe Portable Document Format
Description:
Thesis file
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.74 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Open Theses and Dissertations