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Modelling and Inference using Locally Stationary Processes: Biomedical applications
Rachele Anderson
eSSENCE: The e-Science Collaboration
Mathematical Statistics
Statistical Signal Processing Group
Research output
:
Thesis
›
Licentiate Thesis
146
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Dive into the research topics of 'Modelling and Inference using Locally Stationary Processes: Biomedical applications'. Together they form a unique fingerprint.
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Mathematics
Modeling
100%
Locally Stationary Process
100%
Statistical Dispersion
33%
Data Set
16%
Stochastics
16%
Regression Analysis
16%
Square Regression
16%
Optimal Time
16%
Estimated Model Parameter
16%
Parameter Estimation
16%
Illustrative Example
16%
Statistical Method
16%
Subproblem
16%
Welch Method
16%
Computer Science
Modeling
100%
Process Model
50%
Simulation Study
33%
Least Squares Method
16%
Covariance Matrix
16%
Parameter Estimation
16%
And-States
16%
Spectral Estimation
16%
Information Signal
16%
Nonstationary Signal
16%