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Book Synopsis
In the first chapter, Dr Christian Hugo Hoffmann presents a study that adds to the current knowledge on financial risk and complexity while drawing on the concept of organized complexity, coined by Weaver. He finishes by explaining the correlation between the ideas of complexity, randomness, and systemic risks. In the second chapter, Peter A. Stubberud, Stephen C Stubberud, and Allen R. Stubberud present a signal processing technique, which is a simplification of the dynamic element matching technique, or DEMT and is referred to as the dynamic system matching technique, or DSMT, for controlling the noise signal in the output of a system due to manufacturing errors. In the third and final chapter, Yu Zhou, Weigang Wu, and Huaguan Li define new system models to describe the dynamicity of clusters and then, based on those models, they design and present an algorithm that is able to elect an eventual leader.

Dynamic Systems: Modeling, Performance &

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A Hardback by Marshall Hines

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    View other formats and editions of Dynamic Systems: Modeling, Performance & by Marshall Hines

    Publisher: Nova Science Publishers Inc
    Publication Date: 01/10/2017
    ISBN13: 9781536125573, 978-1536125573
    ISBN10: 1536125571

    Description

    Book Synopsis
    In the first chapter, Dr Christian Hugo Hoffmann presents a study that adds to the current knowledge on financial risk and complexity while drawing on the concept of organized complexity, coined by Weaver. He finishes by explaining the correlation between the ideas of complexity, randomness, and systemic risks. In the second chapter, Peter A. Stubberud, Stephen C Stubberud, and Allen R. Stubberud present a signal processing technique, which is a simplification of the dynamic element matching technique, or DEMT and is referred to as the dynamic system matching technique, or DSMT, for controlling the noise signal in the output of a system due to manufacturing errors. In the third and final chapter, Yu Zhou, Weigang Wu, and Huaguan Li define new system models to describe the dynamicity of clusters and then, based on those models, they design and present an algorithm that is able to elect an eventual leader.

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