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—The algorithm based on KFDA and SVM is proposed. The information of width and angle is extracted from the human motion image sequences. The features of width and angle is merged and reduced by the KPCA. The Low-dimensional gait characteristic is extracted by modified KFDA, which can obtain the best projection direction and enhance the capacity of data(More)
—The algorithm based on KPDA and SVM is proposed. Firstly, Gait Energy Image (GEI) and Moment Gait Energy Images (MGEI) are combined for expressing objects and features reduction. Then the Low-dimensional gait characteristic is extracted by KFDA, which can obtain the best projection direction and enhance the capacity of data classification. Then the support(More)
The gait recognition algorithm adopt support vector machine based on hybrid kernel function and Parameter Optimization. Partial kernel function and overall kernel function are fitted to compose super-kernel function, so that the SVM obtain better generalization ability and generalization ability. In terms of parameter selection, the text uses the objective(More)
For batch processes, a complete batch trajectory can be obtained until the end of its operation. Besides, there are not enough fault data used to build models in historical dataset. Those make it very difficult to diagnose faults for batch processes based on Fisher discriminant analysis (FDA). In order to solve those problems a multi-model Fisher(More)
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