Sensor Selection by Greedy Method for Linear Dynamical Systems: Comparative Study on Fisher-Information-Matrix, Observability-Gramian and Kalman-Filter-Based Indices
Objective functions for sensor selection are investigated in linear time-invariant systems with a large number of sensor candidates. This study compared the performance of sensor sets obtained using three types of D-optimality-based indices as objective functions for sensor selection based on the gr...
Main Authors: | Shun Takahashi, Yasuo Sasaki, Takayuki Nagata, Keigo Yamada, Kumi Nakai, Yuji Saito, Taku Nonomura |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10171363/ |
Similar Items
-
Effect of Objective Function on Data-Driven Greedy Sparse Sensor Optimization
by: Kumi Nakai, et al.
Published: (2021-01-01) -
Efficient Sensor Node Selection for Observability Gramian Optimization
by: Keigo Yamada, et al.
Published: (2023-06-01) -
Greedy Sensor Selection for Weighted Linear Least Squares Estimation Under Correlated Noise
by: Keigo Yamada, et al.
Published: (2022-01-01) -
On the Rate of Convergence of Greedy Algorithms
by: Vladimir Temlyakov
Published: (2023-06-01) -
Community detection with Greedy Modularity disassembly strategy
by: Heru Cahya Rustamaji, et al.
Published: (2024-02-01)