Название: Data-Driven Identification of Networks of Dynamic Systems Автор: Michel Verhaegen, Chengpu Yu, Baptiste Sinquin Издательство: Cambridge University Press Год: 2022 Страниц: 279 Размер: 10,29 МБ Формат: PDF Язык: English
This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.
Big Mechanisms in Systems Biology Название: Big Mechanisms in Systems Biology Автор: Bor-Sen Chen and Cheng-Wei Li Издательство: Academic Press Год: 2016 Формат: PDF Размер: 91 Мб ...
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Data-Driven Identification of Networks of Dynamic Systems 
