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A method of detecting weak signals embedded in chaotic noise by selective support vector machine ensemble based on the theory of phase space reconstruction of the complicated nonlinear system is presented. For improving the generalization ability of support vector machine ensemble, K-means algorithm is used to select the most accurate individual support vector machine from every cluster for ensembling It is established a one-step predictive model that detects the weak signal, including transient signal and period is signals, from the predictive error in the chaotic sequences. It is illustrated in the experiment which is conducted to detect weak signals from Lorenz chaotic background and IPIX Sea Clutter, that the proposed method is highly effective to detect weak signal from a chaotic background and to minimize the influence of noise on weak signals, Compared wich the RBF neural network and SVM model, the new method presents great value in predicting accuracy and detection threshold.
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Keywords:
- support vector machine /
- ensemble /
- clutter /
- weak signal estimation
[1] Haykin S, Li X B 1995 Proceedings IEEE 83 95
[2] Zhang J S, Xiao X C 2000 Acta Phys. Sin.49 403 (in Chinese) [张家树, 肖先赐 2000 49 403]
[3] Xing H Y, Xu W 2007 Acta Phys. Sin. 56 3771 (in Chinese) [行鸿彦, 徐伟 2007 56 3771]
[4] Zhang J F, Hu S S 2007 Acta Phys. Sin. 56 713 (in Chinese) [张军峰, 胡寿松 2007 56 713]
[5] Cui W Z, Zhu C C, Bao W X, Liu J H 2004 Acta Phys. Sin. 53 3303 (in Chinese) [崔万照, 朱长纯, 保文星, 刘君华 2004 53 3303]
[6] Zhou Z H, Wu J X 2002 Artif. Intell 137 239
[7] Grassberger P, Procaccia I 1983 Phys. Rev. Lett. 50 346
[8] Cao L Y 1997 Physica D110 43
[9] Kaplan D T, Glass L 1992 Phys. Rev. Lett. 68 427
[10] Aguirre L A 1995 Phys. Lett. A 203 88
[11] Kim H S, Eykholt R, Salas J D 1999 Physica D 127 48
[12] Takens F 1981 Lecture Notes in Mathematics 898 366
[13] Leo B 1996 Mach. Learn. 21 123
[14] Zhang L, Zhou W, Jiao L 2004 IEEE Trans. Syst. Man Cyb. B 34 34
[15] Wu J X, Zhou Z H, Shen X H, Chen Z Q 2000 J. Comput. Res. Dev. 37 2000 (in Chinese) [吴建鑫, 周志华, 沈学华, 陈兆乾 2000 计算机研究与发展 37 2000]
[16] Kanungo T, Mount D M, Netanyahu N S, Piatko C D, Silverman R, Wu A Y 2002 IEEE Trans. Pattern Anal. Mach. Intell. 24 881
[17] Xing H Y, Jin T L 2010 Acta Phys. Sin. 59 140 (in Chinese) [行鸿彦, 金天力 2010 59 140]
[18] Du J Y, Hou Y B 2007 J. Sci. Instru. 28 555 (in Chinese) [杜京义, 侯媛彬 2007 仪器仪表学报 28 555]
[19] Wang F Y, Yuan G N, Xie Y J, Qiao X W 2009 Radar. Sci. Technol. 7 53 (in Chinese) [王福友, 袁赣南, 谢燕军, 乔相伟 2009 雷达科学与技术 7 53]
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[1] Haykin S, Li X B 1995 Proceedings IEEE 83 95
[2] Zhang J S, Xiao X C 2000 Acta Phys. Sin.49 403 (in Chinese) [张家树, 肖先赐 2000 49 403]
[3] Xing H Y, Xu W 2007 Acta Phys. Sin. 56 3771 (in Chinese) [行鸿彦, 徐伟 2007 56 3771]
[4] Zhang J F, Hu S S 2007 Acta Phys. Sin. 56 713 (in Chinese) [张军峰, 胡寿松 2007 56 713]
[5] Cui W Z, Zhu C C, Bao W X, Liu J H 2004 Acta Phys. Sin. 53 3303 (in Chinese) [崔万照, 朱长纯, 保文星, 刘君华 2004 53 3303]
[6] Zhou Z H, Wu J X 2002 Artif. Intell 137 239
[7] Grassberger P, Procaccia I 1983 Phys. Rev. Lett. 50 346
[8] Cao L Y 1997 Physica D110 43
[9] Kaplan D T, Glass L 1992 Phys. Rev. Lett. 68 427
[10] Aguirre L A 1995 Phys. Lett. A 203 88
[11] Kim H S, Eykholt R, Salas J D 1999 Physica D 127 48
[12] Takens F 1981 Lecture Notes in Mathematics 898 366
[13] Leo B 1996 Mach. Learn. 21 123
[14] Zhang L, Zhou W, Jiao L 2004 IEEE Trans. Syst. Man Cyb. B 34 34
[15] Wu J X, Zhou Z H, Shen X H, Chen Z Q 2000 J. Comput. Res. Dev. 37 2000 (in Chinese) [吴建鑫, 周志华, 沈学华, 陈兆乾 2000 计算机研究与发展 37 2000]
[16] Kanungo T, Mount D M, Netanyahu N S, Piatko C D, Silverman R, Wu A Y 2002 IEEE Trans. Pattern Anal. Mach. Intell. 24 881
[17] Xing H Y, Jin T L 2010 Acta Phys. Sin. 59 140 (in Chinese) [行鸿彦, 金天力 2010 59 140]
[18] Du J Y, Hou Y B 2007 J. Sci. Instru. 28 555 (in Chinese) [杜京义, 侯媛彬 2007 仪器仪表学报 28 555]
[19] Wang F Y, Yuan G N, Xie Y J, Qiao X W 2009 Radar. Sci. Technol. 7 53 (in Chinese) [王福友, 袁赣南, 谢燕军, 乔相伟 2009 雷达科学与技术 7 53]
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