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Support vector machine (SVM) which overcomes the drawbacks of neural networks has been widely used for pattern recognition in recent years. A new optimization method for the fault diagnosis model is proposed. To overcome the deficiencies of low accuracy and high false alarm rate in fault diagnosis system, an integrated fault diagnosis model based on support vector regression and principal components...
The alcoholism is one of psychiatric phenotype, which results from interplay between genetic and environmental factors. Not only it leads to brain defects but also associated cognitive, emotional, and behavioral impairments. It can be detected by analyzing EEG signals. In this research, the power spectrum of the Haar mother wavelet is extracted as features. Then the principle component analysis is...
In this paper, we first propose a method to transform from LDA to PCA with the discriminative information embedded in a whitening transformation, and then we propose a simple support vector machine formulation to LDA. The results of experiments of face recognition conducted on ORL database show the effectiveness of the proposed method.
This paper proposes a new face recognition approach by using Independent Component Analysis (ICA) and Ensemble Classifiers based on Support Vector Machine (SVM). Firstly, to improve the quality of the face images, a series of image pre-processing techniques are used. Then the ICA based on Kernel Principal Component Analysis (KPCA) and FastICA is employed to extract features. At last, appropriate classifiers...
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