Sensor-Based Filtering of Stochastic Distributed Parameter Systems
2015 ◽
Vol 740
◽
pp. 229-233
Keyword(s):
This Paper Proposes a Scheme for Filtering of Stochastic Distributed Parameter Systems. it is Assumed that a Real-Time Environment Consists of m Groups of Sensors, each of which Provides Necessarily State Spatially Measurements from Sensing Devices. Base on Lyapunov Stability Theorem and Itô formula, a Class of Distributed Adaptive Filters with Penalty Terms Result in the State Errors Forming a Stable Evolution System and Asymptotically Converge to Stochastic Distributed Parameter Systems, and then the Preferable State Estimation is Derived. Numerical Simulation Demonstrates the Effectiveness of the Proposed Method.
2006 ◽
Vol 16
(04)
◽
pp. 1041-1047
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Keyword(s):
1979 ◽
Vol 15
(1)
◽
pp. 33-40
2008 ◽
Vol 9
(2)
◽
pp. 71-78
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1970 ◽
Vol 290
(1)
◽
pp. 49-59
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