陶亮.基于活跃集迭代法的支持向量机快速增量算法[J].系统仿真学报,2006,18(11):3305-3312.TAO Liang.Fast incremental SVM learning algorithm based on active set iterations[J].Journal of System Simulation,2006,18(11):3305-3312.(in Chinese)
[4]
杨涛,谢剑英.一种片率增量SVM多用户检测器算法仿真研究[J].系统仿真学报,2004,16(10):2185-2188.YANG Tao,XIE Jian-ying.A chip-increment support machine-based algorithm for multi-user detection[J].Journal ofSystem Simulation,2004,16(10):2185-2188.(in Chinese)
[5]
KNERR S,PERSONNAZ L,DREYFUS G.Single-layer learning revisited:a stepwise procedure for building and training aneural network[C]∥Neurocomputing:Algorithms,Architectures and Applications.New York:Springer-Verlag,1999:667-670.
[6]
李东晖,杜树新,吴铁军.基于壳向量的线性支持向量机快速增量学习算法[J].浙江大学学报:工学版,2006,40(2):203-207.LI Dong-hui,DU Shu-xin,WU Tie-jun.Fast incremental learning algorithm of linear support vector machine based on hullvectors[J].Journal of Zhejiang University:Engineering Science,2006,40(2):203-207.(in Chinese)
[7]
SYED N,LIU H,SUNG K.Handling incremental learning with support vector machines[C]∥Proc Workshop on SupportVector Machines at the International Joint Conference on Artificial Intelligence(i-ICAI99).Stockholm,Sweden:MorganKaufmann,1999:458-462.
[8]
普雷帕拉塔,沙莫斯.计算几何导论[M].庄心谷,译.北京:科学出版社,1990:183-187.
[9]
邓乃扬,田英杰.数据挖掘中的新方法:支持向量机[M].北京:科学出版社,2004.
[10]
王瑞平,陈杰,山世光,等.基于支持向量机的人脸检测训练集增强[J].软件学报,2008,19(11):2921-2931.WANG Rui-ping,CHEN Jie,SHAN Shi-guang,et al.Enhancing training set of face detection based on SVM[J].Journalof Software,2008,19(11):2921-2931.(in Chinese)
[11]
武方方,赵银亮.基于尺度核函数的最小二乘支持向量机[J].模式识别与人工智能,2006,19(5):598-603.WU Fang-fang,ZHAO Yin-liang.Lease squares support vector machine based on scaling kernel function[J].PatternRecognition and Artificial Intelligence,2006,19(5):598-603.(in Chinese)
[12]
ESKIN E,ARNOLD A,PRERAU M,et al.A geometric framework for unsupervised anomaly detection:detectingintrusions in unlabeled data[M]∥Applications of Data Mining in Computer Security.New York:Kluwer,2002.