Information Complexity and Statistical Modeling in High Dimensions with Applications



Information complexity criterion in the Gaussian graphical model: real data applications
Bülbül, Gül Bahar; Purutçuoğlu Gazi, Vilda (2018-07-03)
Information theory, entropy and urban spatial structure
Esmer, Özcan; Türel, Ali; Department of City and Regional Planning (2005)
Urban planning has witnessed the profound changes in the methodologies of modelling during the last 50 years. Spatial interaction models have passed from social physics, statistical mechanics to non-spatial and spatial information processing stages of progress that can be designated as paradigm shifts. This thesis traces the Maximum Entropy (MaxEnt) approach in urban planning as pioneered by Wilson (1967,1970) and Spatial Entropy concept by Batty (1974) based on the Information Theory and its developments b...
Information Recovery-based Model Reference Adaptive Control for Fast Adaptation and Improved Transients with Aerospace Applications
Yayla, Metehan; Kutay, Ali Türker; Department of Aerospace Engineering (2023-2-13)
This thesis proposes improvements to Filter-based Model Reference Adaptive Control (MRAC) architectures for uncertain dynamical systems. Standard MRAC cannot guarantee closed-loop stability in the presence of bounded perturbations without restrictive persistent excitation of system signals. Robust modifications have been introduced to increase the robustness of standard MRAC and/or guarantee stability without persistent excitation, but little improvement has been achieved in guaranteed transient response. R...
Information Decorrelation for an Interacting Multiple Model Filter
Acar, Duygu; Orguner, Umut (2018-07-13)
In a sensor network compensation of the correlated information caused by previous communication is of utmost interest for distributed estimation. In this paper, we investigate different information decorrelation approaches that can be applied when using an interacting multiple model filter in a local sensor node. The related decorrelation and the corresponding fusion operations are discussed. The different approaches are compared on a simple distributed single maneuvering target tracking example.
Information-centric sensor networks for cognitive IoT: an overview
Al-Turjman, Fadi M. (2017-02-01)
Information-centric sensor networks (ICSNs) are a paradigm of wireless sensor networks that focus on delivering information from the network based on user requirements, rather than serving as a point-to-point data communication network. Introducing learning in such networks can help to dynamically identify good data delivery paths by correlating past actions and results, make intelligent adaptations to improve the network lifetime, and also improve the quality of information delivered by the network to the ...
Citation Formats
V. Purutçuoğlu Gazi, “Information Complexity and Statistical Modeling in High Dimensions with Applications,” 2021, Accessed: 00, 2021. [Online]. Available: