Results 281 to 290 of about 169,139 (307)

Distributed filtering without knowledge of noise distribution

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992
An algorithm of distributed filtering using set models with confidence values is derived. No knowledge of the noise distribution is needed. The only information required is the set with confidence values from which the modeling and measurement errors and the initial values are obtained.
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PCB distributed filters

2019 IEEE Radio and Antenna Days of the Indian Ocean (RADIO), 2019
In this paper, a new family of ceramic resonators and filters is introduced. The proposed resonators are enabled by the integration of distributed resonators into standard Printed Circuit Board (PCB) substrates. This integration caters for not only a tremendous reduction in the resonator profile, but it also enables utilization of the unused PCB real ...
Senad Bulja, Florian Pivit, Dmitry Kozlov   +2 more
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Distributed Kalman Filtering With Adaptive Communication

IEEE Control Systems Letters
This letter proposes an adaptive event-triggered communication framework for distributed state estimation in sensor networks, enabling each node to self-adapt its transmission rule while maintaining a desired average rate and complying with an upper bound on individual transmission rates.
Daniela Selvi, Giorgio Battistelli
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Tapered Distributed Filters

IRE Transactions on Circuit Theory, 1962
The study of distributed networks has been prompted by the trend in electronic equipment toward smaller and smaller physical structures. Various investigators have determined the network characteristics of rather complex distributed RC structures. It is the purpose of this paper to point out the effects of geometrical tapering on the characteristics of
W. Kaufman, S. Garrett
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Distribution in a particle filter

Target Tracking 2004: Algorithms and Applications, 2004
Particle filters are the state-of-the-art solution to difficult tracking problems. The crucial step in the efficient application of particle filters to specific problems is the design of the proposal distribution. This proposal distribution defines how the particles are propagated from one time step to the next.
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Consensus optimization approach for distributed Kalman filtering: Performance recovery of centralized filtering

Automatica, 2023
Kunhee Ryu, Juhoon Back
exaly  

Distributed non-fragile set-membership filtering for nonlinear systems under fading channels and bias injection attacks

International Journal of Systems Science, 2021
Lifeng Ma, Yuming Bo
exaly  

Distributed filtering

International Journal of Systems Science, 1992
openaire   +1 more source

Distributed filtering based on Cauchy-kernel-based maximum correntropy subject to randomly occurring cyber-attacks

Automatica, 2022
Derui Ding, Hongli Dong, Xiaojian Yi
exaly  

Distributed set-membership filtering for time-varying systems: A coding–decoding-based approach

Automatica, 2021
Shuai Liu, Lifeng Ma, Yuming Bo
exaly