Thesis (M. App. Sc.)--University of Adelaide, Dept. of Applied Mathematics, 1993? / Includes bibliographical references (leaves 92-93).

Thesis (M.S. in electrical engineering)--Washington State University, May 2010. / Title from PDF title page (viewed on July 23, 2010). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 55-57).

<p>The design and analyses of Space-Time Block Codes (STBC) for both single antenna and two-antenna distributed relay channels are considered in this thesis. Due to the fact that the equivalent channel gains for two-phase relay channels are the product of two channel coefficients, many current STBC designs for Multiple Input Multiple Output (MIMO) channels cannot be implemented to distributed relay channels efficiently. The direct application of Orthogonal Space-Time Block Coding (OSTBC) for MIMO systems to distributed cooperative relay networks makes the equivalent channel matrix for maximum likelihood (ML) detection lose its orthogonality. Hence, a new design that makes the channel matrix be \textit{orthogonally distributed} (OD) for a suboptimal symbol-by-symbol detector (SBSD) is proposed in this thesis. With ODSTBC, an asymptotic symbol error probability (SEP) formula with SBSD is derived, showing the optimal diversity gain function for single antenna distributed relay channels $\frac{\ln^N\rho}{\rho^N}$ is achieved. In addition, two ODSTBC designs for the distributed relay networks are presented, which interestingly renders that SBSD is equivalent to the ML detector. The ODSTBC enjoys both optimal diversity function and low detection complexity. However, the symbol rate of ODSTBC is relatively low in order to maintain the orthogonal conditions. To address this problem, another Alamouti Based Toeplitz Space-Time Block Code (ABTSTBC) for two-antenna distributed relay channels is proposed. Both the code structure and the equivalent channel matrix has a block Toeplitz structure, whose blocks are the addition and product of two Alamouti matrices, respectively. With the linear SBSD, the optimal diversity function $\frac{\ln^N\rho}{\rho^{2N}}$ is achieved. At the same time, the advantages of low computational complexity and high symbol rate are maintained. Numerical results verify the diversity analyses and indicate competitive error performance to currently available distributed STBC designs with much lower complexity.</p> / Master of Applied Science (MASc)

Forest fires constantly threaten ecological systems, infrastructure and human lives. The purpose behind this study is minimizing the devastating damage caused by forest fires. Since it is impossible to completely avoid their occurrences, it is essential to accomplish a fast and appropriate intervention to minimize their destructive consequences. The most traditional method for detecting forest fires is human based surveillance through lookout towers. However, this study presents a more modern technique. It utilizes land-based real-time multispectral video processing to identify and determine the possibility of fire occurring within the camera’s field of view. The temporal, spectral, and spatial signatures of the fire are exploited. The methods discussed include: (1) Range filtering followed by entropy filtering of the infrared (IR) video data, and (2) Principal Component Analysis of visible spectrum video data followed by motion analysis and adaptive intensity threshold. The two schemes presented are tailored to detect the fire core, and the smoke plume, respectively. Cooled Midwave Infrared (IR) camera is used to capture the heat distribution within the field of view. The fire core is then isolated using texture analysis techniques: first, range filtering applied on two consecutive IR frames, and then followed by entropy filtering of their absolute difference. Since smoke represents the earliest sign of fire, this study also explores multiple techniques for detecting smoke plumes in a given scene. The spatial and temporal variance of smoke plume is captured using temporal Principal Component Analysis, PCA. The results show that a smoke plume is readily segmented via PCA applied on the visible Blue band over 2 seconds sampled every 0.2 seconds. The smoke plume exists in the 2nd principal component, and is finally identified, segmented, and isolated, using either motion analysis or adaptive intensity threshold. Experimental results, obtained in this study, show that the proposed system can detect smoke effectively at a distance of approximately 832 meters with a low false-alarm rate and short reaction time. Applied, such system would achieve early forest fire detection minimizing fire damage. Keywords: Image Processing, Principal Component Analysis, PCA, Principal Component, PC, Texture Analysis, Motion Analysis, Multispectral, Visible, Cooled Midwave Infrared, Smoke Signature, Gaussian Mixture Model.

The objective of this thesis is to formulate and solve the sensor placement problem for damage localization in a sensor network. A Bayesian estimation problem is formulated with the time-of-flight (ToF) measurements. In this model, ToF of lamb waves, which are generated and received by piezoelectric sensors, is the total time for each wave to be transmitted, reflected by the target, and received by the sensor. The ToF of the scattered lamb wave has characteristic information about the target location. By using the measurement model and prior information, the target location is estimated in a centralized sensor network with a Monte Carlo approach. Then we derive the Bayesian Fisher information matrix (B-FIM) and based on that posterior Cramer-Rao lower bound (PCRLB), which sets a limit on the mean squared error (MSE) of any Bayesian estimator. In addition, we develop an optimal sensor placement approach to achieve more accurate damage localization, which is based on minimizing the PCRLB. Simulation results show that the optimal sensor placement solutions lead to much lower estimation errors than some sub-optimal sensor placement solutions.

Thesis (Ph.D.)--University of Texas at Arlington, 2008.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, March 2003. / Thesis advisor(s): Monique P. Fargues. Includes bibliographical references (p. 105-106). Also available online.

Thesis (Ph. D.) -- California Institute of Technology, 2010. / Title from home page (viewed 03/03/2010). Advisor and committee chair names found in the thesis' metadata record in the digital repository. Includes bibliographical references.

Thesis (M.S. in Electrical Engineering)--Washington State University. / Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 158-161). Available also in a digital version from Dissertation Abstracts.