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A novel semi-supervised algorithm based on co-training is proposed in this paper. In the method, the motion energy history image are used as the different feature representation of human action; then the co-training based semi-supervised learning algorithm is utilized to predict the category of unlabeled training examples. And the average motion energy and history images are calculated as the recognition model for each category action. When recognition, the observed action is firstly classified through its correlation coefficients to the prior established templates respectively; then its final category is determined according to the consistency between the classification results of motion energy and motion history images. The experiments on Weizmann dataset demonstrate that our method is effective for human action recognition.

A novel human action recognition algorithm based on key posture is proposed in this paper. In the method, the mesh features of each image in human action sequences are firstly calculated; then the key postures of the human mesh features are generated through k-medoids clustering algorithm; and the motion sequences are thus represented as vectors of key postures. The component of the vector is the occurrence number of the corresponding posture included in the action. For human action recognition, the observed action is firstly changed into key posture vector; then the correlevant coefficients to the training samples are calculated and the action which best matches the observed sequence is chosen as the final category. The experiments on Weizmann dataset demonstrate that our method is effective for human action recognition. The average recognition accuracy can exceed 90%.

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Based on the brushless DC motor system with DC-link small capacitance powered by a single-phase AC power source, a boosting DC-link voltage strategy to reduce the commutation torque ripple of brushless DC motors is proposed in this paper. The control strategy utilizes the special topology of the motor system to boost the DC-link capacitor voltage in a specific zone during the non-commutation period. During the commutation period, the high voltage of the DC-link capacitor is released to meet the voltage requirement of the brushless DC motor during commutation. In order to reduce the commutation torque ripple and ensure the normal operation of the brushless DC motor, each rectifier cycle is divided into three zones according to the characteristics of the periodic change of the rectifier output voltage. Different operation modes are proposed for different zones. In DC-link capacitor boost voltage mode, the DC-link capacitor boosts the voltage to meet the voltage of the motor demand during the commutation period for achieving the purpose of reducing the commutation torque ripple. In this paper, the controller of the brushless DC motor system is designed and the experimental platform is built. The experimental results verified the correctness of the theoretical analysis and the feasibility of the proposed method.