Signal estimation and reconstruction at sub-Nyquist rates.

dc.contributor.authorSaab, Mohamad Hassan
dc.contributor.departmentDepartment of Electrical and Computer Engineering
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture
dc.contributor.institutionAmerican University of Beirut
dc.date2019
dc.date.accessioned2020-03-28T16:41:51Z
dc.date.available2022-05
dc.date.available2020-03-28T16:41:51Z
dc.date.issued2019
dc.date.submitted2019
dc.descriptionThesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2019. ET:7017.
dc.descriptionAdvisor : Dr. Karim Kabalan, Professor, Electrical and Computer Engineering ; Co-Advisor : Dr. Youssef Nasser, Senior Lecturer, Electrical and Computer Engineering ; Members of Committee : Dr. Ali Chehab, Professor, Electrical and Computer Engineering ; Dr. Mohammad Mansour, Professor, Electrical and Computer Engineering.
dc.descriptionIncludes bibliographical references (leaves 34-39)
dc.description.abstractFrequency estimation is a very important step to correctly detect a signal components. Nowadays, frequency estimation is required in many applications such biomedical signals, spectrum sensing, and military systems. However, as most of these applications require wide bands signals, the implementation of conventional sampling schemes at the Nyquist rate becomes very challenging. Hence, it is primordial to propose advanced frequency estimation methods at subNyquist sampling rates. In literature, Chinese remainder theorem (CRT) has been proposed to estimate the components of a single frequency signal. However, its extension to multiple components has not been addressed due to the complexity of the estimation algorithm. In this proposal, we extend the CRT further by proposing a new approach for frequency estimation of a signal with multiple components as long as they have a particular pattern. The results have been validated by Monte-Carlo simulations and compared with the well-known MUSIC algorithm.
dc.format.extent1 online resource (x, 39 leaves) : illustrations (some color)
dc.identifier.otherb23584154
dc.identifier.urihttp://hdl.handle.net/10938/21813
dc.language.isoen
dc.subject.classificationET:007017
dc.subject.lcshAlgorithms.
dc.subject.lcshSignal processing -- Digital techniques.
dc.subject.lcshChinese remainder theorem.
dc.subject.lcshMonte Carlo method.
dc.titleSignal estimation and reconstruction at sub-Nyquist rates.
dc.typeThesis

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
et-7017.pdf
Size:
818.75 KB
Format:
Adobe Portable Document Format