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In ensemble learning, a higher accuracy can be achieved by integrating some classifiers instead of all the classifiers. But, it is very difficult to select the best classifier combination which can be seen as an optimization problem, from a pool of classifiers. To deal with this problem, we propose a new classifier selection method, Sorting-based Dynamic Classifier Ensemble Selection (SDES), which...
Brain-computer interface (BCI) system uses brain activity to control external devices such as computers and electronic devices. It is a novel kind of human computer interaction. BCI system can be regard as pattern recognition system, and the key point is classification of Electroencephalogram (EEG) signals under different mental tasks. Classification algorithms of BCI system include Fisher linear...
Fuzzy C-Means (FCM) algorithm is an unsupervised fuzzy clustering method. Clustering results accuracy of the algorithm is affected by equal partition trend of the data sets. When amount of each cluster sample are difference greatly, the optimal solution of the algorithm may not be the correct partition of the data sets. Weighted Fuzzy C-Means (WFCM) algorithm is proposed to overcome this disadvantage...
As an important link of pattern recognition, pattern feature extraction and selection has been paid close attention by lots of scholars, and currently become one of the research hot spot in the field of pattern recognition. Its main purpose is ldquolow loss dimensionality reductionrdquo; it is generally divided into two parts, that is, linear pattern feature extraction and selection and nonlinear...
Supervised anomaly intrusion detection systems (IDSs) based on Support Vector Machines (SVMs) classification technique have attracted much more attention today. In these systems, features of instances and the characteristic of kernels have great influence on learning and predict results. However, selecting feasible features and kernel parameters can be time-consuming as the number of features and...
Ground targets are constrained on the Earth with their velocity vector direction aligned mostly along the body longitudinal axis. The pose angle therefore carries kinematic information useful for tracking maneuvering targets. For target identification (ID), range profiles obtained by a high range resolution (HRR) radar are compared with reference templates in pose angle per target class, thus producing...
An integrated autonomous target acquisition system using a passive sensor suite is presented in this paper. The system configuration and various functional subsystems are described. The emphasis of the paper is placed on the fusion of heterogeneous sensor data which are asynchronous based upon Dempster-Shafer's rule of combination. Preliminary results of target feature analysis, clustering, and classification...
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