Sparse approximation based on wavelet kernel support vector machines

被引：0
|
作者：
Yang, DK [1 ]
Tong, YB [1 ]
Zhang, QS [1 ]
机构：
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100083, Peoples R China
来源：
PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年
关键词：
wavelet kernel function; support vector machine; sparse approximation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel support vector machines, which can converge to minimum error with better sparsity. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.
引用
收藏
页码：4249 / 4253
页数：5
相关论文
共 50 条
  • [1] WAVELET KERNEL SUPPORT VECTOR MACHINES FOR SPARSE APPROXIMATION
    Tong Yubing Yang Dongkai Zhang Qishan (Dept of Electronic Information Engineering
    Journal of Electronics(China), 2006, (04) : 539 - 542
  • [2] WAVELET KERNEL SUPPORT VECTOR MACHINES FOR SPARSE APPROXIMATION
    Tong Yubing Yang Dongkai Zhang Qishan Dept of Electronic Information Engineering Beijing University of Aeronautics and astronautics Beijing China
    Journal of Electronics, 2006, (04) : 539 - 542
  • [3] Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso
    Aliquintuy, Marcelo
    Frandi, Emanuele
    Nanculef, Ricardo
    Suykens, Johan A. K.
    PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2016, 2017, 10125 : 208 - 216
  • [4] SUPPORT VECTOR MACHINES BASED ON THE ORTHOGONAL PROJECTION KERNEL OF FATHER WAVELET
    Zhang, Li
    Zhou, Weida
    Jiao, Licheng
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS, 2005, 5 (03) : 283 - 303
  • [5] An equivalence between sparse approximation and support vector machines
    Girosi, F
    NEURAL COMPUTATION, 1998, 10 (06) : 1455 - 1480
  • [6] On support vector machines and sparse approximation for random processes
    Capobianco, E
    NEUROCOMPUTING, 2004, 56 : 39 - 60
  • [7] Sparse approximation using least squares support vector machines
    Suykens, JAK
    Lukas, L
    Vandewalle, J
    ISCAS 2000: IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS - PROCEEDINGS, VOL II: EMERGING TECHNOLOGIES FOR THE 21ST CENTURY, 2000, : 757 - 760
  • [8] Support Vector Machines Based Composite Kernel
    Ma, Dingkun
    Yang, Xinquan
    Kuang, Yin
    2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION PROBLEM-SOLVING (ICCP), 2015, : 432 - 435
  • [9] SINC-CAUCHY HYBRID WAVELET KERNEL FOR SUPPORT VECTOR MACHINES
    George, Jose
    Rajeev, K.
    2008 IEEE WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 2008, : 356 - +
  • [10] Support Vector machines for Automatic target recognition using wavelet kernel
    Zhao, Jiong
    Fan, Yang-Yu
    Liu, Yuan-Kui
    2007 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1-4, PROCEEDINGS, 2007, : 1424 - 1427
12345