Here f denotes the objective function to be minimized with respect to Θ and F signifies the model function corresponding to the measured data set η = (η1, η2,..., η n ) T consisting of measured C labeling data (xm).
The dependence of these precursors on the size of the measured data set and the time required for their computation is investigated.
However, as the measured data set grows, it becomes difficult to accurately extract the mode and its parameters because of noise and non-stationary phenomena.
According to this study, the differences between the respective TMY data sets and long-term measured data set (measured with percentage root mean square error – %RMSE) are bigger than 5%.
Comparative results are obtained by using both an approximate sinusoidal current velocity data set simulating periods of real flow and a sea trial measured data set containing highly-turbulent and velocity-sheared flow in a semi-physical test.
Statistical downscaling approaches use both the spatially downscaled grids and measured data for the same period to adjust the 4-km grids so that certain statistical properties, in this case the mean and standard deviation, are the same as the measured data set.
First, normal (Gaussian) distributions were constructed for every measured data set in Table 3, subject to the known mean and standard deviation of each point.
Several backscattering geometry related issues are: (1) The estimation of the clean image of the homogeneous host medium from the measured data set obtained at an array of scanning positions can not be obtained simply by averaging the measured data set.
In order to reduce the computational time of the inverse problem, it has been recently proposed to compress the measured data set by using a Fourier [ 7, 8] or wavelets [ 9] encoding.
The image for a target-free host medium is not available in most applications and must be generated from the measured data set of the medium with targets embedded inside.
