Thesis. 1978. Sc.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Vita. / Bibliography: p. 142-145. / Sc.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by John Newland Ratzel. / Ph.D.

by Wong Yin Shung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 62-64). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.7 / Chapter 2 --- Fundamentals --- p.9 / Chapter 2.1 --- Representation of a digital image --- p.9 / Chapter 2.2 --- Salt-and-pepper --- p.10 / Chapter 2.3 --- Resolution of a gray digital image --- p.11 / Chapter 3 --- Filters --- p.14 / Chapter 3.1 --- Median filter --- p.15 / Chapter 3.2 --- Adaptive median filter --- p.15 / Chapter 3.3 --- Multi-state median filter --- p.16 / Chapter 3.4 --- Directional difference-based switching median filter --- p.18 / Chapter 3.5 --- Improved switching median filters --- p.20 / Chapter 3.6 --- Variational method --- p.21 / Chapter 3.7 --- Two-phase method --- p.22 / Chapter 4 --- New Two Phase Methods --- p.25 / Chapter 4.1 --- Triangule-based interpolation --- p.25 / Chapter 4.1.1 --- Delaunay triangulation --- p.26 / Chapter 4.1.2 --- Linear interpolation --- p.28 / Chapter 4.1.3 --- Cubic interpolation --- p.29 / Chapter 4.2 --- Gradient estimation --- p.32 / Chapter 4.3 --- Regularization method --- p.33 / Chapter 4.3.1 --- Least square method with Laplacian regularization --- p.33 / Chapter 4.3.2 --- Lagrange multipliers --- p.35 / Chapter 4.4 --- Fast transform for finding the inverse of Laplacian matrix --- p.38 / Chapter 5 --- Inpainting and Zooming --- p.39 / Chapter 5.1 --- Inpainting --- p.39 / Chapter 5.2 --- Zooming --- p.40 / Chapter 5.2.1 --- Bilinear interpolation --- p.40 / Chapter 5.2.2 --- Bicubic interpolation --- p.41 / Chapter 6 --- Results --- p.46 / Chapter 6.1 --- Results of denoising --- p.47 / Chapter 6.2 --- Results of inpainting --- p.47 / Chapter 6.3 --- Results of zooming --- p.48 / Chapter 6.4 --- Conclusions --- p.51

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Bibliography: p. 235-239. / by Jere Schenck Meserole, Jr. / Ph.D.

Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Vita. / Includes bibliographical references. / by Joseph Edward Wall, Jr. / Ph.D.

As one of the social relations, "distrust" also performs an important role in online Web sites. We also observe that distrust information can also be incorporated to improve recommendation quality. Hence, the last part of this thesis studies the problem on how to improve recommender system by considering explicit distrust information among users. We make the assumption that users' distrust relations can be interpreted as the "dissimilar" relations since user ui distrusts user ud indicates that user ui disagrees with most of the opinions issued by user ud. Based on this intuition, the distrust relations between users can be easily modeled by adding the regularization term into the objective functions of the user-item matrix factorization. The experiments on the Epinions dataset indicate that distrust information is at least as important as trust information. / However, the data sparsity problem of the involved user-item matrix seriously affects the recommendation quality. Many existing approaches to recommender systems cannot easily deal with users who have made very few ratings. The objective of this thesis is to study how to build effective and efficient approaches to improve the recommendation performance. / In this thesis, we first propose two collaborative filtering methods which only utilize the user-item matrix for recommendations. The first method is a neighborhood-based collaborative filtering method which designs an effective missing data prediction algorithm to improve recommendation quality, while the second one is a model-based collaborative filtering method which employs matrix factorization technique to make the recommendation more accurate. / In view of the exponential growth of information generated by online users, social contextual information analysis is becoming important for many Web applications. Hence, based on the assumption that users can be easily influenced by the friends they trust and prefer their friends' recommendations, we propose two recommendation algorithms by incorporating users' social trust information. These two methods are based on probabilistic matrix factorization. The complexity analysis indicates that our approaches can be applied to very large datasets since they scale linearly with the number of observations, while the experimental results show that our methods perform better than the state-of-the-art approaches. / Recommender Systems are becoming increasingly indispensable nowadays since they focus on solving the information overload problem, by providing users with more proactive and personalized information services. Typically, recommender systems are based on Collaborative Filtering, which is a technique that automatically predicts the interest of an active user by collecting rating information from other similar users or items. Due to their potential commercial values and the associated great research challenges, Recommender systems have been extensively studied by both academia and industry recently. / Ma, Hao. / "December 2009." / Advisers: Irwin King; Michael R. Lyu. / Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 136-154). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Event related potentials (ERP's) carry very important information that relates to the performance of the brain functions of the human being. Further studies have identified that one component, in particular, P 300, is affected by the memory process. Matched filter is used to improved the SNR of signal ERP' s. We use the output of the matched filter to distinguish the difference of the waveforms between normal subjects and memory-impaired subjects. In our study, we found that the peak values of the matched filtering output were different between normal subjects and memoryimpaired subjects. Also, as an application, wavelet transform is introduced to the ERP analysis. Local maximum of wavelet transform was used as a local feature to find the relationship between the sharp variation points and the memory process. A comparison between matched filtering and wavelet transform was made and also the correlation coefficients of the peaks and sharp variation points are calculated to find the relationship between the important moments in a memory process.

[by] Bernard Gold and Lawrence R. Rabiner. / Bibliography: p. 36. / Contract DA 28-043-AMC-02536(E). Project no. 200-14501-B31F.

Thesis (Ph. D.)--York University, 2001. Graduate Programme in Computer Science. / Typescript. Includes bibliographical references (leaves 132-142). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pNQ66340

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