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For enhancing fault diagnosis precision, the wavelet packet analysis and least squares support vector machine are combined effectively. First, the signals are decomposed in arbitrary minute frequency bands by use of wavelet packet analysis technique. Doing energy calculation in these frequency bands to form eigenvectors is more reasonable. And then a least squares support vector machine fault diagnosis...
In the paper, a vehicle recognition model based on LSSVM is presented. In the model, the non-sensitive loss function is replaced by quadratic loss function and the inequality constraints are replaced by equality constraints. Consequently, quadratic programming problem is simplified as the problem of solving linear equation groups, and the SVM algorithm is realized by least squares method. It is presented...
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