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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A detailed look into two problems on lacunary sequences

Volynin, Ilya. January 2008 (has links)
Thesis (M.S.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 8).
2

Minimizing and stationary sequences.

January 1999 (has links)
by Wong Oi Ping. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 77-79). / Abstracts in English and Chinese. / Chapter 1 --- LP-minimizing and Stationary Sequences --- p.8 / Chapter 1.1 --- Residual function --- p.8 / Chapter 1.2 --- Minimizing sequences --- p.14 / Chapter 1.3 --- Stationary sequences --- p.17 / Chapter 1.4 --- On the equivalence of minimizing and stationary se- quence --- p.21 / Chapter 1.5 --- Complementarity conditions --- p.25 / Chapter 1.6 --- Subdifferential-based stationary sequence --- p.29 / Chapter 1.7 --- Convergence of an Iterative Algorithm --- p.32 / Chapter 2 --- Minimizing And Stationary Sequences In Nonsmooth Optimization --- p.38 / Chapter 2.1 --- Subdifferential --- p.38 / Chapter 2.2 --- Stationary and minimizing sequences --- p.40 / Chapter 2.3 --- C-convex and BC-convex function --- p.43 / Chapter 2.4 --- Minimizing sequences in terms of sublevel sets --- p.44 / Chapter 2.5 --- Critical function --- p.48 / Chapter 3 --- Optimization Conditions --- p.52 / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Second-order necessary and sufficient conditions with- out constraint --- p.55 / Chapter 3.3 --- The Lagrange and G-functions in constrained problems --- p.63 / Chapter 3.4 --- Second-order necessary conditions for constrained prob- lems --- p.73 / Chapter 3.5 --- Sufficient conditions for constrained problems --- p.74 / Bibliography
3

Higher-order Markov chain models for categorical data sequences

Fung, Siu-leung., 馮紹樑. January 2003 (has links)
published_or_final_version / abstract / toc / Mathematics / Master / Master of Philosophy
4

High-dimensional Markov chain models for categorical data sequences with applications

Fung, Siu-leung., 馮紹樑. January 2006 (has links)
published_or_final_version / abstract / Mathematics / Doctoral / Doctor of Philosophy
5

Kernel based methods for sequence comparison.

January 2011 (has links)
Yeung, Hau Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 59-63). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.7 / Chapter 2 --- Work Flows and Kernel Methods --- p.9 / Chapter 2.1 --- Work Flows --- p.9 / Chapter 2.2 --- Frequency Vector --- p.11 / Chapter 2.3 --- Motivation for Kernel Based Distance --- p.12 / Chapter 2.3.1 --- Similarity between sequences --- p.13 / Chapter 2.3.2 --- Distance between sequences --- p.14 / Chapter 2.4 --- Kernels for DNA Sequence --- p.15 / Chapter 2.4.1 --- Kernels based on evolution model --- p.15 / Chapter 2.4.2 --- Kernels based on empirical data --- p.17 / Chapter 2.5 --- Kernels for Peptide Sequence --- p.18 / Chapter 3 --- Dataset for DNA Sequence and Results --- p.25 / Chapter 3.1 --- Dataset and Goal --- p.25 / Chapter 3.1.1 --- Mitochondrial DNA dataset --- p.26 / Chapter 3.1.2 --- 18S ribosomal RNA --- p.28 / Chapter 3.2 --- Results --- p.28 / Chapter 4 --- Dataset for Peptide Sequence and Results --- p.35 / Chapter 4.1 --- Dataset and Goal --- p.36 / Chapter 4.2 --- Classification and Evaluation Methods --- p.39 / Chapter 4.2.1 --- Partition of training and testing datasets --- p.39 / Chapter 4.2.2 --- Classification methods --- p.40 / Chapter 4.3 --- Results --- p.45 / Chapter 4.3.1 --- KNN performs better than the FDSM --- p.45 / Chapter 4.3.2 --- BLOSUM62 performs best and window length not important --- p.46 / Chapter 4.3.3 --- Distance formula (2.4) performs better --- p.49 / Chapter 5 --- Discussion --- p.51 / Chapter 5.1 --- Sequence Length and Window Length --- p.51 / Chapter 5.2 --- Possible Kernels --- p.52 / Chapter 5.3 --- Distance Formulae --- p.53 / Chapter 5.4 --- Protein Structural Problem --- p.54 / Chapter 6 --- Appendix --- p.55 / Chapter 6.1 --- Kernel for Peptide Sequences --- p.55 / Bibliography --- p.59
6

High-dimensional Markov chain models for categorical data sequences with applications

Fung, Siu-leung. January 2006 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.
7

Eine Untersuchung der Anwendbarkeit rekurrenter Reihen zur Aufsuchung versteckter Periodizitäten

Armstrong, Gordon Nelson. January 1913 (has links)
Thesis (doctoral)--K. Technischen Hochschule zu München, 1913. / Includes bibliographical references.
8

On potentially (K₄--e)-graphic sequences

Niu, Jianbing. January 1900 (has links)
Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains iii, 27 p. Includes abstract. Includes bibliographical references (p. 26-27).
9

Limit periodicity of sequences defined by certain recurrence relations; and Julia sets

Herndon, John Alan 05 1900 (has links)
No description available.
10

Dependence and limit theorems for stationary infinitely divisible sequences

Harrelson, Dyana Rae 08 1900 (has links)
No description available.

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