State Estimation for a Carbon Nanotube-based Sensor Array System

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This paper proposes state estimation methods for tracking a time-varying local concentration of target molecules from the carbon-nanotube (CNT)-based sensing system. The signals triggered by adsorption/desorption events of a trace of the proximate target molecules on the sensors show strongly stochastic behavior. Various state estimation methods including the Kalman filter (KF), particle filter (PF), and moving horizon estimator (MHE) are designed for the system with highly stochastic, non-Gaussian measurements.
Publisher
ICROS
Issue Date
2015-10-15
Language
English
Citation

ICCAS 2015

URI
http://hdl.handle.net/10203/210567
Appears in Collection
CBE-Conference Papers(학술회의논문)
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