Gauss process state-space model optimization algorithm with expectation maximization
A Gauss process state-space model trained in a laboratory cannot accurately simulate a nonlinear system in a non-laboratory environment. To solve this problem, a novel Gauss process state-space model optimization algorithm is proposed by combining the expectation–maximization algorithm with the Gaus...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2019-07-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/1550147719862217 |