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Jing Zhou

    Täter-Opfer-Ausgleich im Rahmen eines Strafverfahrens in China und Deutschland in rechtsvergleichender Sicht
    Feature selection in data mining
    Electronic properties of model molecular electronics and catalyst
    Adaptive Backstepping Control of Uncertain Systems with Actuator Failures, Subsystem Interactions, and Nonsmooth Nonlinearities
    • 2020

      Focusing on advanced control systems, this book presents innovative methodologies for designing and analyzing adaptive backstepping control systems. It addresses critical challenges such as actuator failures, subsystem interactions, and nonsmooth nonlinearities. Additionally, the text explores significant open issues in areas like adaptive failure accommodation, decentralized adaptive control, and distributed adaptive coordinated control, making it a valuable resource for researchers and practitioners in the field.

      Adaptive Backstepping Control of Uncertain Systems with Actuator Failures, Subsystem Interactions, and Nonsmooth Nonlinearities
    • 2012

      Electronic properties of model molecular electronics and catalyst

      Electronic structures of organic molecules on metal surface and size-selected clusters on oxide surface

      • 172 pages
      • 7 hours of reading

      Focusing on the electronic structures of adsorbed molecules, this book explores two key systems. The first involves phenyl diisocyanide molecules forming one-dimensional chains on a metal surface, leading to unique interfacial electronic properties that could enhance molecular conductors in nanoelectronics. The second system examines MoxSy clusters on an alumina film, revealing that increased cluster coverage raises the local work function due to electron tunneling, suggesting innovative modifications for the electronic structure and reactivity of heterogeneous catalysts.

      Electronic properties of model molecular electronics and catalyst
    • 2007

      In many predictive modeling tasks, one has a fixed set of observations from which a vast, or even infinite, set of potentially predictive features can be computed. Of these features, often only a small number are expected to be useful in a predictive model. Models which use the entire set of features will almost certainly overfit on future data sets. The book presents streamwise feature selection which interleaves the process of generating new features with that of feature testing. Streamwise feature selection scales well to large feature sets. The book also describes how to use streamwise feature seleciton in multivariate regressions. It includes a review of traditional feature selecitions in a general framework based on information theory, and compares these methods with streamwise feature selection on various real and synthetic data sets. This book is intended to be used by researchers in machine learning, data mining, and knowledge discovery.

      Feature selection in data mining