The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.
For modeling mobile data communications, we have Data Activity, Data Activity On, DataConOn, and GSMRSSI predictors.
This study attempts to determine the FCO predictors as elaborate in Fig. 1.
On the negative side, the accuracy of HB predictors is highly path-dependent.
Radial and sigmoid based SVM predictors outperformed polynomial and linear kernels significantly (p < 0.05).
A methodology based on spectral similarity is presented that allows to compare NMR predictors without the recourse to assigned experimental spectra, thereby making the task of benchmarking NMR predictors less tedious, faster, and less prone to human error.
In this work, chaotic modeling of sea clutter is realized by fitting these two components with RBF predictors separately.
In our previous work on cooperative prediction [93], we extended prediction error performance analysis for HMM predictors [83].
The figure demonstrates that GP predictors provides a better prediction with respect to simply using the profiles of similar wards.
Therefore, we will use transcendental time functions as LF predictors to control for periodic autocorrelation in our multivariate trend model.
