Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints

ISBN-13: 9781032038179 / Angielski / Twarda / 2021 / 222 str.

Jinling Liang; Zidong Wang; Fan Wang

Opis

It presents research developments and novel methodologies for recursive filtering for 2-D shift-varying systems with communication constraints. It investigates recursive filter/estimator design and performance analysis explaining dynamics of the system, subtle design of filter gains, effects of the communication constraints on performance.

Spis treści

1. Introduction. 2. Minimum-Variance Recursive Filtering for Two-Dimensional Systems with Degraded Measurements: Boundedness and Monotonicity. 3. Robust Kalman Filtering for Two-Dimensional Systems with Multiplicative Noises and Measurement Degradations. 4. Robust Finite-Horizon Filtering for Two-Dimensional Systems with Randomly Varying Sensor Delays. 5. Recursive Filtering for Two-Dimensional Systems with Missing Measurements subject to Uncertain Probabilities. 6. Resilient State Estimation for Two-Dimensional Shift-Varying Systems with Redundant Channels. 7. Recursive Distributed Filtering for Two-Dimensional Shift-Varying Systems Over Sensor Networks Under Random Access Protocols. 8. Resilient Filtering for Linear Shift-Varying Repetitive Processes under Uniform Quantization and Round-Robin Protocols. 9. Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes. 10. Conclusions and Future Topics.