Set inversion via interval analysis for nonlinear bounded-error estimation
Automatica (Journal of IFAC) - Special section on fault detection, supervision and safety for technical processes
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Linear Optimal Control Systems
Linear Optimal Control Systems
An Efficient Algorithm for Solving Distributed State Estimator and Laboratory Implementation
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Volume 01
Efficient 16-bit Floating-Point Interval Processor for Embedded Systems and Applications
SCAN '06 Proceedings of the 12th GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic and Validated Numerics
Sensor networks and distributed CSP: communication, computation and complexity
Artificial Intelligence - Special issue: Distributed constraint satisfaction
IEEE Transactions on Signal Processing
SOI-KF: Distributed Kalman Filtering With Low-Cost Communications Using the Sign of Innovations
IEEE Transactions on Signal Processing
The design space of wireless sensor networks
IEEE Wireless Communications
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This paper presents distributed bounded-error parameter and state estimation algorithms suited to measurement processing by a network of sensors. Contrary to centralized estimation, where all data are collected to a central processing unit, here, each data is processed locally by the sensor, the results are broadcasted to the network and taken into account by the other sensors. A first analysis of the conditions under which distributed and centralized estimation provide the same results has been presented. An application to the tracking of a moving source using a network of sensors measuring the strength of the signal emitted by the source is considered.