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Record Nr. |
UNINA9910556894303321 |
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Autore |
Han Fei (Mathematician) |
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Titolo |
Distributed Filtering, Control and Synchronization : Local Performance Analysis Methods / / by Fei Han, Zidong Wang, Hongli Dong |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
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ISBN |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (231 pages) : illustrations (chiefly color) |
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Collana |
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Studies in Systems, Decision and Control, , 2198-4190 ; ; 428 |
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Disciplina |
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Soggetti |
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Automatic control |
Signal processing |
Telecommunication |
Stochastic processes |
Control and Systems Theory |
Signal, Speech and Image Processing |
Communications Engineering, Networks |
Stochastic Systems and Control |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Distributed H-infinity Filtering for Discrete-Time Piecewise Linear Systems -- Consensus Filtering with Stochastic Nonlinearities and Multiple Missing Measurements -- Distributed Filtering for Random Parameter System with Event-Triggering Protocols -- Scalable Consensus Filtering for Uncertain Systems with Round-Robin Protocol -- Partial-Nodes-Based Scalable H-infinity-Consensus Filtering with Censored Measurements -- Distributed H-infinity-Consensus Filtering over Sensor Networks under Deception Attacks -- Distributed Resilient Filtering for Time-Delayed Systems with Stochastic Perturbations -- Finite-Horizon H-infinity-Consensus Control for Multi-Agent Systems with Random Parameters -- Bounded H-infinity Synchronization and H-infinity Filtering for Discrete-Time Complex Networks. |
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Sommario/riassunto |
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This book establishes a unified framework for dealing with typical engineering complications arising in modern, complex, large-scale |
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networks such as parameter uncertainties, missing measurement and cyber-attack. Distributed Filtering, Control and Synchronization is a timely reflection on methods designed to handle a series of control and signal-processing issues in modern industrial engineering practice in areas like power grids and environmental monitoring. It exploits the latest techniques to handle the emerging mathematical and computational challenges arising from, among other things, the dynamic topologies of distributed systems and in the context of sensor networks and multi-agent systems. These techniques include recursive linear matrix inequalities, local-performance and stochastic analyses and techniques based on matrix theory. Readers interested in the theory and application of control and signal processing will find much to interest them in the new models and methods presented in this book. Academic researchers can find ideas for developing their own research, graduate and advanced undergraduate students will be made aware of the state of the art, and practicing engineers will find methods for addressing practical difficulties besetting modern networked systems. |
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