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Signal estimation and reconstruction at sub-Nyquist rates.

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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


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