Variance-Constrained Filtering for Stochastic Complex Systems Theories and Algorithms /
This book is concerned with the variance-constrained optimized filtering problems and their potential applications for nonlinear time-varying dynamical systems. The distinguished features of this book are highlighted as follows. (1) A unified framework is provided for handling the variance-constrain...
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| Auteurs principaux: | , , |
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| Collectivité auteur: | |
| Format: | Électronique eBook |
| Langue: | anglais |
| Publié: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2025.
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| Édition: | 1st ed. 2025. |
| Collection: | Intelligent Control and Learning Systems,
18 |
| Sujets: | |
| Accès en ligne: | https://doi.org/10.1007/978-981-96-2637-3 |
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Table des matières:
- Introduction
- Recursive Filtering and Boundedness Analysis with ROQ
- Resilient Filtering with Stochastic Uncertainties and Incomplete Measurements
- Event-Triggered Resilient Filtering with Stochastic Uncertainties and SPDs
- Event-triggered Filtering with Missing Measurements
- Fault Estimation Against Randomly Occurring Deception Attacks
- Fault Estimation with Packet Dropouts and ROUs
- Fault Estimation with Randomly Occurring Faults and Sensor Saturations
- State Estimation for Complex Networks with Missing Measurements
- Quantized State Estimation for Complex Networks with Uncertain Inner Coupling
- Event-Based State Estimation for Complex Networks under UOPs
- Event-Based State Estimation for Complex Networks with Fading Observations and UST
- State Estimation for Complex Networks with Uncertain Observations and Coupling Strength
- Conclusions and Future Work.