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	Large margin distribution multi-class supervised novelty detection 期刊论文 OAI收割 EXPERT SYSTEMS WITH APPLICATIONS, 2023, 卷号: 224, 页码: 119937 作者: Zhu, Fa; Zhang, Wenjie; Chen, Xingchi; Gao, Xizhan; Ye, Ning \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2023/05/06 Novelty detection Multi-class supervised novelty detection Margin distribution Margin theory Large margin distribution-supervised novelty detection
	The aircraft autopilot design of parameters changing in a wide range (EI CONFERENCE) 会议论文 OAI收割 2011 International Conference on Electric Information and Control Engineering, ICEICE 2011, April 15, 2011 - April 17, 2011, Wuhan, China Zhen D.; Yue Z. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 Autopilot is an important part of aircraft Under the action of the disturbance torque for the flight parameters of aircraft Changing in a wide range the range was about 16km on the basic of analyzing the typical trajectory the max height was about 5100m the trajectory of feature points were selected the deviation of lateral was about 12m taking pitch control loop for example the maximum angle of attack was about 3.6 a sub- PID autopilot was designed using classical control theory the maximum elevator deflection was less than 5 using single-mode Transient suppression method the maximum aileron deflection was less than 2 the overload due to control surface transition deflection was avoided when control parameters changing the maximum roll was less than 5 the verification was done by non-linear simulation. The result showed that: the phase margin of autopilot was greater than 30 the response of overload can accurately track the given overload instruction. An autopilot design method of aircraft of parameter changes in a wide range was provided. 2011 IEEE. the bandwidth was more than 14rad / s the settling time was less than 0.7s the maximum overshoot was 23.3%
	Learning linear PCA with convex semi-definite programming 期刊论文 OAI收割 PATTERN RECOGNITION, 2007, 卷号: 40, 期号: 10, 页码: 2633-2640 作者: Tao, Qing; Wu, Gao-wei; Wang, Jue 收藏 \| 浏览/下载：22/0 \| 提交时间：2015/11/08 principal component analysis statistical learning theory support vector machines margin maximal margin algorithm semi-definite programming robustness
	Learning linear PCA with convex semi-definite programming 期刊论文 OAI收割 PATTERN RECOGNITION, 2007, 卷号: 40, 期号: 10, 页码: 2633-2640 作者: Tao, Qing; Wu, Gao-wei; Wang, Jue \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2019/12/16 principal component analysis statistical learning theory support vector machines margin maximal margin algorithm semi-definite programming robustness
	Posterior probability support vector Machines for unbalanced data Neural Networks 期刊论文 OAI收割 IEEE Transactions on Neural Networks, 2005, 卷号: 16, 期号: 6, 页码: 1561-1573 作者: Qing Tao; Gao-Wei Wu; Fei-Yue Wang; Jue Wang \| 收藏 \| 浏览/下载：35/0 \| 提交时间：2017/07/15 Bayesian Decision Theory Classification Margin Maximal Margin Algorithms -svm Posterior Probability Support Vector Machines (Svms) Unbalanced Data.
	Posterior probability support vector Machines for unbalanced data Neural Networks 期刊论文 OAI收割 IEEE Transactions on Neural Networks, 2005, 卷号: 16, 期号: 6, 页码: 1561-1573 作者: Qing Tao; Gao-Wei Wu; Fei-Yue Wang; Jue Wang; - \| 收藏 \| 浏览/下载：138/0 \| 提交时间：2017/07/15 Bayesian Decision Theory Classification Margin Maximal Margin Algorithms -svm Posterior Probability Support Vector Machines (Svms) Unbalanced Data.
	Posterior probability support vector machines for unbalanced data 期刊论文 OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS, 2005, 卷号: 16, 期号: 6, 页码: 1561-1573 作者: Tao, Q; Wu, GW; Wang, FY; Wang, J \| 收藏 \| 浏览/下载：32/0 \| 提交时间：2019/12/16 Bayesian decision theory classification margin maximal margin algorithms v-SVM posterior probability support vector machines (SVMs) unbalanced data
	A new maximum margin algorithm for one-class problems and its boosting implementation 期刊论文 OAI收割 PATTERN RECOGNITION, 2005, 卷号: 38, 期号: 7, 页码: 1071-1077 作者: Tao, Q; Wu, GW; Wang, J 收藏 \| 浏览/下载：20/0 \| 提交时间：2015/11/06 one-class problems outliers statistical learning theory support vector machines margin boosting
	有关分类问题的统计学习理论与算法研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2002 王家琦收藏 \| 浏览/下载：51/0 \| 提交时间：2015/09/02 Bayes 统计学习理论 PAC 泛化经验风险特征映射核边缘间隔投影 SVM Boosting Bayes Statistical Learning Theory PAC generalization empirical risk margin feature mapping kernel SVM Boosting