Application of local polynomial estimation in suppressing strong chaotic noise
In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay emb...
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| Published in | Chinese physics B Vol. 21; no. 2; pp. 181 - 186 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
01.02.2012
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-1056 2058-3834 1741-4199 |
| DOI | 10.1088/1674-1056/21/2/020508 |
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| Abstract | In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low. |
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| AbstractList | In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low. |
| Author | 苏理云 马艳菊 李姣军 |
| AuthorAffiliation | School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054, China School of Electronic Information and Automation, Chongqing University of Technology, Chongqing 400054, China |
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| CitedBy_id | crossref_primary_10_1155_2015_901807 crossref_primary_10_1155_2014_101230 crossref_primary_10_1155_2012_696927 crossref_primary_10_1155_2015_329487 crossref_primary_10_4236_jcc_2014_212004 crossref_primary_10_7498_aps_66_090503 crossref_primary_10_1007_s11277_017_4275_3 crossref_primary_10_7498_aps_73_20231343 crossref_primary_10_4236_ojs_2012_23043 crossref_primary_10_1155_2012_201678 crossref_primary_10_1155_2019_4842102 crossref_primary_10_12677_SA_2015_42008 |
| Cites_doi | 10.1088/1674-1056/19/3/030506 10.1016/S0020-0255(98)10026-9 10.1103/PhysRevA.45.3403 10.7498/aps.58.2220 10.1155/2010/605241 10.7498/aps.52.526 10.1088/1009-1963/16/11/013 10.7498/aps.60.020508 10.1007/s11277-007-9312-1 10.1007/978-3-642-01507-6_94 10.1109/TCSI.2003.812606 10.1155/2011/930958 10.1088/1674-1056/20/2/020505 10.1016/j.camwa.2009.10.019 |
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| Notes | In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low. Su Li-Yun, Ma Yan-Ju, Li Jiao-Jun a） School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054, China b） School of Electronic Information and Automation, Chongqing University of Technology, Chongqing 400054, China strong chaotic noise, local polynomial estimation, weak signal detection 11-5639/O4 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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| References | 13 14 You R Y (8) 2011; 20 Meng Q F (12) 2007; 16 Zhang C T (9) 2011; 60 Mao J Q (11) 2009; 58 Su L Y (16) 2011; 2011 Li Y (1) 2003; 52 Guan Y (3) 2003; 50 Su L Y (15) 2010; 2010 Su L Y (5) 2007; 39 Nie C Y (2) 2009 6 7 Deng K (4) 2010; 19 Fan J Q (17) 2005 10 |
| References_xml | – start-page: 23 year: 2009 ident: 2 publication-title: Chaotic System and Weak Signal Detection – volume: 19 start-page: 030506 issn: 1674-1056 year: 2010 ident: 4 publication-title: Chin. Phys. doi: 10.1088/1674-1056/19/3/030506 – ident: 7 doi: 10.1016/S0020-0255(98)10026-9 – ident: 6 doi: 10.1103/PhysRevA.45.3403 – volume: 58 start-page: 2220 issn: 0372-736X year: 2009 ident: 11 publication-title: Acta Phys. Sin. doi: 10.7498/aps.58.2220 – volume: 2010 start-page: 605241 year: 2010 ident: 15 publication-title: Math. Probl. Eng. doi: 10.1155/2010/605241 – volume: 52 start-page: 526 issn: 0372-736X year: 2003 ident: 1 publication-title: Acta Phys. Sin. doi: 10.7498/aps.52.526 – volume: 16 start-page: 3220 issn: 1009-1963 year: 2007 ident: 12 publication-title: Chin. Phys. doi: 10.1088/1009-1963/16/11/013 – volume: 60 start-page: 020508 issn: 0372-736X year: 2011 ident: 9 publication-title: Acta Phys. Sin. doi: 10.7498/aps.60.020508 – ident: 13 doi: 10.1007/s11277-007-9312-1 – ident: 10 doi: 10.1007/978-3-642-01507-6_94 – volume: 50 start-page: 945 year: 2003 ident: 3 publication-title: IEEE T. Circ. doi: 10.1109/TCSI.2003.812606 – volume: 39 start-page: 149 year: 2007 ident: 5 publication-title: J. Sichuan Univ. (Eng. Sci.) – volume: 2011 start-page: 930958 year: 2011 ident: 16 publication-title: Discrete Dyn. Nat. Soc. doi: 10.1155/2011/930958 – volume: 20 start-page: 020505 issn: 1674-1056 year: 2011 ident: 8 publication-title: Chin. Phys. doi: 10.1088/1674-1056/20/2/020505 – ident: 14 doi: 10.1016/j.camwa.2009.10.019 – start-page: 51 year: 2005 ident: 17 publication-title: Nonlinear Time Series |
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| SubjectTerms | Chaos theory Delay Mathematical analysis Mean square values Noise Polynomials Retarding Simulation Time series 估计方法 信号干扰比 多元时间序列 局部多项式 应用 有用信号 混沌噪声 相空间重构 |
| Title | Application of local polynomial estimation in suppressing strong chaotic noise |
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