Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


Alkhateeb_Dissertation_11_05_2017.pdf (1.27 MB)

ETD Abstract Container

Abstract Header

DATA-DRIVEN UNCERTAINTY QUANTIFICATION IN APPLICATIONS OF ELECTROMAGNETICS AND WIRELESS COMMUNICATION VIA ARBITRARY POLYNOMIAL CHAOS

Alkhateeb, Osama
http://rave.ohiolink.edu/etdc/view?acc_num=akron1509988525627307

Abstract Details

, Doctor of Philosophy, University of Akron, Electrical Engineering.
In the last two decades, polynomial chaos expansion (PCE) methods have received considerable attention due to their efficiency and accuracy in modelling stochastic processes. However, implementing these methods require specifying the input distributions of a model a priori. This might not be feasible in data-driven applications in which the inputs are represented as data samples obtained from real-time measurements. Further, fitting the data with parametric distributions may introduce undesirable errors. The arbitrary polynomial chaos (aPC) method overcomes this limitation by constructing a chaos expansion based on the statistical moments rather than the probability distributions. The first objective of this dissertation is to develop a procedure based on aPC for data-driven uncertainty quantification (UQ) in applications of electromagnetics and wireless communication. Although the aPC method is considered to be simple and effective, it becomes numerically unstable when high-order expansions are sought. Alternatively, the multi-element arbitrary polynomial chaos (ME-aPC) alleviates this drawback by replacing the aPC expansion with a piecewise reduced order one. The second objective of this dissertation is to develop a procedure based on ME-aPC, and to demonstrate its efficiency in data-driven UQ. The proposed procedures are implemented with several model problems of electromagnetics such as filters and sensors, and with model problems of wireless communications addressing uncertainties in lunar radio links. The accuracy of the procedures is validated with plots of relative error, and in some examples, with results obtained via the classical Monte Carlo (MC) method.
Nathan Ida (Advisor)
Igor Tsukerman (Committee Member)
Hamid Bahrami (Committee Member)
Pan Ernian (Committee Member)
Malena Espanol (Committee Member)
Electrical Engineering; Electromagnetics

Recommended Citations

Citations

  • Alkhateeb, O. (n.d.). DATA-DRIVEN UNCERTAINTY QUANTIFICATION IN APPLICATIONS OF ELECTROMAGNETICS AND WIRELESS COMMUNICATION VIA ARBITRARY POLYNOMIAL CHAOS [Doctoral dissertation, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1509988525627307

    APA Style (7th edition)

  • Alkhateeb, Osama. DATA-DRIVEN UNCERTAINTY QUANTIFICATION IN APPLICATIONS OF ELECTROMAGNETICS AND WIRELESS COMMUNICATION VIA ARBITRARY POLYNOMIAL CHAOS . University of Akron, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1509988525627307.

    MLA Style (8th edition)

  • Alkhateeb, Osama. "DATA-DRIVEN UNCERTAINTY QUANTIFICATION IN APPLICATIONS OF ELECTROMAGNETICS AND WIRELESS COMMUNICATION VIA ARBITRARY POLYNOMIAL CHAOS ." Doctoral dissertation, University of Akron. Accessed APRIL 19, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=akron1509988525627307

    Chicago Manual of Style (17th edition)

akron1509988525627307
453
© , all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.