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This paper presents a motor function rehabilitation system for the disabled with virtual reality. The design of the entire system is established on the SIGVerse virtual platform. The patient can complete the rehabilitation training immersed in a virtual environment. Firstly, the motion information of the patient is recognized by Kinect, and regenerated by the avatar in the virtual environment accurately...
In this paper, a novel approach for online motor fault diagnosis is proposed based on artificial neural network (ANN) trained by immune clustering and genetic algorithm (IGA). The IGA is employed to adaptively optimize the structure of the radial basis function neural network (RBFNN). The clonal selection principle is responsible for how the centres will represent the training data set. The immune...
Motor fault diagnosis methods are crucial in acquiring safe and reliable operation in motor drive systems. In this paper, a new method for the motor fault diagnosis is proposed based on wavelet packet transform (WPT) and artificial neural network (ANN). The energy of the vibration signals of motor can be obtained by the multi-decomposition of WPT and used as feature values of ANN inputs for fault...
Motor fault diagnosis methods are crucial in acquiring safe and reliable operation in motor drive systems. In this paper, we propose a hybrid algorithm for motor fault diagnosis based on the combination of artificial immune system (AIS) and artificial neural network (ANN). The artificial immune algorithm (AIA) for data clustering is employed to adaptively choose the amount and location of the hidden...
As an important step of content based news video retrieving and intelligence mining, semantic unit segmentation has attracted many researcherspsila interests. This paper focuses on a new method of news video stories segmentation which is based on the announcerspsila voiceprints. Firstly, the voiceprints included acoustic perception characteristics of all announcers have been extracted, and its Gaussian...
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