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Credit risk analysis is to determine if a customer is likely to default on the financial obligation. In this paper, we will introduce sparse non-negative matrix factorization method to discovery the lower dimensional space for reducing the data dimensionality, which will contribute to good performance and fast computation in the credit risk classification performed by support vector machine. We test...
We introduce a novel method, named S-CRP (Segmentation based on distance dependent Chinese Restaurant Process), to segment broadcast sports videos into semantic shots. S-CRP employs distance dependent Chinese Restaurant Process (DCRP) using two segmentation criteria, namely appearance and time distances. It takes advantage of the customer (frame) assignments in DCRP and is able to reduce the negative...
A comparison of two passivity-based control strategies — with and without an integral control action — is proposed in this paper for the tracking control of a hydrostatic transmission, which is commercially used in working machines. An unknown leakage volume flow and a resulting load torque are taken into account as lumped disturbances. These disturbances and two unmeasurable state variables — the...
In order to improve the system accuracy of fault diagnosis, this paper proposes the integrated fault diagnosis method based on multi-SVM classifiers. MultiBoost integrated learning method using the AdaBoost algorithm and Wagging algorithm composed of multiple integrated with a combination of base classifiers to improve the classification accuracy of the system. The simulation results show that the...
A comparison of two decentralised backstepping control strategies - with and without an integral part - is presented in this paper for the tracking control of a hydrostatic drive train, which is commercially used in working machines. An unknown leakage volume flow and a resulting load torque are taken into account as lumped disturbances. These disturbances and two unmeasurable state variables - the...
During the course of sound source localization, the localization system often misoperates because of the environment noise, sensors' failure and other reasons. And there are outliers in the measurements because of the clutter environment. To solve this problem, this paper present a new Kalman filter based on outliers for sound source localization. By adaptively adjusting the measurement noise covariance...
In the actual course of target tracking, the measurement noise is changing at any time because of the impact of external environment, the problem of the sensors system and other reasons. Meanwhile, there are outliers in the measurements because of the clutter environment. However, the measurement noise covariance is changeless in standard Kalman filter, and the impact of outliers on the tracking results...
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