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The model parameters were estimated via maximum likelihood (ML) estimation, using AMOS 7.0.
The new project is called "Image Scale Estimation Using Genetic Programming in Java".
We illustrate sample size estimation using a real application example.
This approach enables coherence estimation using temporal, pixel-based evaluation.
We first validated the probability density estimation using Fourier inversion.
CNC estimation using Pushbroom Hyperspectral Imager (PHI) airborne hyperspectral data.
It was presented uncertainty estimation using two methods.
3D rotation estimation using vector measurements is investigated.
In the table, ML denotes ML estimation using a sliding window with detections, and ML denotes ML estimation using a sliding window with a fixed length.
Two design methods for robust fault estimation using switched filters are proposed.
The interfacial characteristics are investigated through microstructural examination and quantitative estimation using strengthening models.
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