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- 2Gaussian Process
- 1Dynamic modeling
- 1EM algorithm
- 1Flat-topped Gaussian Distribution
- 1Mixture of Gaussian distributions
- 1Noisy input
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Spring 2016
In data-driven modelling, model accuracy relies heavily on the data set collected from target process. However, various types of measurement noise exist extensively in industrial processes and the data obtained are usually contaminated. If the influence of measurement noise is neglected, both the...
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Robust Gaussian Process Regression with a mixture of two Gaussian distributions as a noise model
DownloadSpring 2018
Increasingly many complex processes from the different fields of biological systems, engineering or econometrics are often required to be controlled. Hence, in such cases, we deal with identification of underlying complex processes which is essential for control design, optimization, and process...
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