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Full-Text Articles in Theory and Algorithms

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh Oct 2022

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale. Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …


Machine Learning With Topological Data Analysis, Ephraim Robert Love May 2021

Machine Learning With Topological Data Analysis, Ephraim Robert Love

Doctoral Dissertations

Topological Data Analysis (TDA) is a relatively new focus in the fields of statistics and machine learning. Methods of exploiting the geometry of data, such as clustering, have proven theoretically and empirically invaluable. TDA provides a general framework within which to study topological invariants (shapes) of data, which are more robust to noise and can recover information on higher dimensional features than immediately apparent in the data. A common tool for conducting TDA is persistence homology, which measures the significance of these invariants. Persistence homology has prominent realizations in methods of data visualization, statistics and machine learning. Extending ML with …


Biological Simulations And Biologically Inspired Adaptive Systems, Edgar Alfredo Duenez-Guzman Dec 2009

Biological Simulations And Biologically Inspired Adaptive Systems, Edgar Alfredo Duenez-Guzman

Doctoral Dissertations

Many of the most challenging problems in modern science lie at the interface of several fields. To study these problems, there is a pressing need for trans-disciplinary research incorporating computational and mathematical models. This dissertation presents a selection of new computational and mathematical techniques applied to biological simulations and problem solving: (i) The dynamics of alliance formation in primates are studied using a continuous time individual-based model. It is observed that increasing the cognitive abilities of individuals stabilizes alliances in a phase transition-like manner. Moreover, with strong cultural transmission an egalitarian regime is established in a few generations. (ii) A …