dc.contributor.author |
Saab, Mohamad Hassan |
dc.date.accessioned |
2020-03-28T16:41:51Z |
dc.date.available |
2022-05 |
dc.date.available |
2020-03-28T16:41:51Z |
dc.date.issued |
2019 |
dc.date.submitted |
2019 |
dc.identifier.other |
b23584154 |
dc.identifier.uri |
http://hdl.handle.net/10938/21813 |
dc.description |
Thesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2019. ET:7017. |
dc.description |
Advisor : 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.description |
Includes bibliographical references (leaves 34-39) |
dc.description.abstract |
Frequency 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.extent |
1 online resource (x, 39 leaves) : illustrations (some color) |
dc.language.iso |
eng |
dc.subject.classification |
ET:007017 |
dc.subject.lcsh |
Algorithms. |
dc.subject.lcsh |
Signal processing -- Digital techniques. |
dc.subject.lcsh |
Chinese remainder theorem. |
dc.subject.lcsh |
Monte Carlo method. |
dc.title |
Signal estimation and reconstruction at sub-Nyquist rates. |
dc.type |
Thesis |
dc.contributor.department |
Department of Electrical and Computer Engineering |
dc.contributor.faculty |
Maroun Semaan Faculty of Engineering and Architecture |
dc.contributor.institution |
American University of Beirut |