Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references (leaves 163-171). Also available in electronic version. Access restricted to campus users.

Thesis (M. S.)--Economics, Georgia Institute of Technology, 2010. / Committee Chair: Kilic, Rehim; Committee Member: Iacopetta, Maurizio; Committee Member: McCarthy, Patrick. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--University of Chicago, Department of Mathematics, June 2002. / Includes bibliographical references. Also available on the Internet.

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n the problem of time delay estimation (TDE), the desired source signals of interest are correlated and with a specific spectral distribution. In such cases, the convergence speed using the conventional approaches, viz., time domain adaptive constrained and unconstrained LMS TDE algorithms, becomes slowly and the performance of TDE will be degraded, dramatically. In fact, the convergence rate depends highly on the distribution of spectral density of the desired signal sources. Also, the performance of TDE is affected by the background noises, accordingly. To circumvent the problem described above, in this thesis, a transformed domain adaptive constrained filtering scheme, refers to the constrained adaptive DCT-LMS algorithm, for TDE is devised. We show that this new proposed constrained algorithm, with the so-called direct delay estimation formula, for non-integer TDE does perform better than the conventional time domain adaptive constrained and unconstrained LMS TDE algorithms and the unconstrained adaptive DCT-LMS TDE algorithm. Finally, to further reduce the spread of eigenvalue in the unconstrained adaptive DCT-LMS algorithm, the Gram-Schmidt orthogonalizer approach realizing by the adaptive Escalator is investigated. It indicates that bias of TDE will occur without using the constraint of weight vector. That is, it could not be used to alleviate the effect due to background noises.

This thesis examines exchange rate exposure of 30 U.S. industries between 1974 and 2008 using traditional and orthogonalized linear models. Similar to the literature, when using traditional linear model we find that exposure is very time dependent and often insignificant. However, we discover that orthogonalization helps uncover more evidence of industry exposure. Within the orthogonalized linear model framework, we find that exposure is statistically and economically important, and the effect of orthogonalization is more pronounced for exposure to currency indices. We also test symmetry in exchange rate exposure by subdividing the sample period into the periods of appreciations and depreciations. Interestingly, we find little evidence that exchange rate is asymmetric even if we use orthogonalized linear model. Lastly, we discover that exchange rate exposure cannot be explained by our international trade data.

Thesis (Ph.D.)--University of Wollongong, 2006. / Typescript. Includes bibliographical references: leaf 216-228.

Thesis (M. App. Sc.)--Carleton University, 2002. / Includes bibliographical references (p. 116-118). Also available in electronic format on the Internet.

Thesis (M. App. Sc.)--Carleton University, 2005. / Includes bibliographical references (p. 179-183). Also available in electronic format on the Internet.