The theory of reproducing kernel Hilbert spaces (RKHSs) has been developed into a powerful tool in mathematics and lots applications many fields, especially machine learning. Fractal provides new technologies for making complicated curves fitting experimental data. Recently, combinations fractal interpolation functions (FIFs) methods curve estimations have attracted the attention researchers. W...

The Support Vector Machine has gained significant popularity over recent years as a kernel-based supervised learning technique. However, choosing the appropriate kernel function and its associated parameters is not a trivial task. The kernel is often chosen from several widely-used and general-purpose functions, and the parameters are then empirically tuned for the best results on a specific da...

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...