Thesis (Ph.D.)--Kent State University, 2010. / Title from PDF t.p. (viewed May 26, 2010). Advisor: Dr. Alfred Cavaretta. Keywords: variation diminishing; convolution; de la vallee poussin. Includes bibliographical references (p.61).

Kwok, Tsz Chiu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 43-45). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.6 / Chapter 1.1 --- Historical remarks and main results --- p.6 / Chapter 1.2 --- Structure of the thesis --- p.8 / Chapter 2 --- Basic properties --- p.10 / Chapter 2.1 --- Existence of infinite convolution --- p.10 / Chapter 2.2 --- Properties --- p.16 / Chapter 2.3 --- Law of pure type --- p.17 / Chapter 3 --- Some results related to pure singularity --- p.20 / Chapter 3.1 --- The Pisot-Vijayaraghavan numbers --- p.20 / Chapter 3.2 --- The Salem numbers --- p.22 / Chapter 3.3 --- The weak separation condition --- p.23 / Chapter 4 --- A proof of almost everywhere absolute continuity --- p.30 / Chapter 5 --- Other results and problems --- p.37 / Chapter 5.1 --- Entropy of Bernoulli convolutions --- p.37 / Chapter 5.2 --- Dimensions --- p.40 / Chapter 5.3 --- Non PV numbers with bad behavior --- p.41 / Chapter 5.4 --- Open problems --- p.41 / Bibliography --- p.43

Thesis (Ph.D.)--University of Central Florida, 2008. / Adviser: Qiyu Sun. On t.p., "l" is small script ell and "p" is superscript. Includes bibliographical references (p. 37-38).

No description available.

Gradient-based junctions form key features in such applications as object classification, motion segmentation, and image enhancement. Asymmetric junctions arise from the merging of an odd number of contour end-points such as at a 'Y' junction. Without an asymmetric representation of such a structure, it will be identified in the same category as 'X' junctions. This has severe consequences when distinguishing between features in object classification, discerning occlusion from disocclusion in motion segmentation and in properly modeling smoothing boundaries in image enhancement. / Current junction analysis methods include convolution, which applies a mask over a sub-region of the image, and diffusion, which propagates gradient information from point-to-point based on a set of rules. / A novel method is proposed that results in an improved approximation of the underlying contours, through the use of asymmetric junctions. The method combines the ability to represent asymmetric information, as do a number of convolution methods, with the robustness of local support obtained from diffusion schemes. This work investigates several different design paradigms of the asymmetric tensor diffusion algorithm. The proposed approach proved superior to existing techniques by properly accounting for asymmetric junctions over a wide range of scenarios.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 61).

This thesis describes a method of transforming a deconvolution problem into an equivalent convolution problem. A short discussion of the theory behind convolution and deconvolution is included, along with a survey of techniques now being used. A new method using a synthesized compensator is proposed and mathematically developed. Finally, the results of applying this method to several real and analytical signals are given.

No description available.

No description available.

published_or_final_version / abstract / Physics / Master / Master of Philosophy