Automatic modulation classification is an essential and challenging topic in the development
of cognitive radios, and it is the cornerstone of adaptive modulation and demodulation …

Tree boosting has empirically proven to be a highly effective approach to predictive
modeling. It has shown remarkable results for a vast array of problems. For many years …

Multiple kernel learning aims at simultaneously learning a kernel and the associated
predictor in supervised learning settings. For the support vector machine, an efficient and …

We consider a general formulation of the multiple change-point problem, in which the data is
assumed to belong to a set equipped with a positive semidefinite kernel. We propose a …

The prediction algorithm is one of the most important factors in the quality of wind-power
prediction. In this paper, based on the principles of wavelet transform and support vector …

This paper presents establishing intelligent system for faults detection and classification of
induction motor using wavelet support vector machine (W-SVM). Support vector machines …

The aim of this paper is twofold. First, a new functional representation of accelerometer data
of a distributional nature is introduced to build a complete individualized profile of each …

Estimating the non-flat function which comprises both the steep variations and the smooth
variations is a hard problem. The results achieved by the common support vector methods …

The automatic diagnosis of lung cancer via artificial intelligence faces two hotspot issues:(1)
insufficient data and (2) excessive redundant information, which make it difficult for …

Regression methods are widely used to estimate the spectral reflectance of object surfaces
from camera responses. These methods are under the same problem setting as that to build …