基于小波包变换的非高斯噪声信号结构分析
The Signal Structure Analysis of Non-Gaussian Noise Based on Wavelet Packet Transform
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摘要: 该文利用小波包变换的时频局部分析能力,研究了非高斯分布平稳随机噪声的统计特性,揭示了 非高斯噪声信号的信号结构。在此基础上,将经典最优检测器的结论推广到背景噪声为非高斯分布的情况, 提出了一种基于小波包变换的非高斯噪声下的信号检测方法。仿真实验验证了该方法是正确的。Abstract: By exploiting wavelet packet transform to analyze signals both in time and frequency space, this paper researches the statistic property of non-Gaussian stationary noise and its signal structure. The results of classic optimum detector arc extended to the condition where the distribution of background noise is non-Gaussian and a new signal detection algorithm in non-Gaussian background noise is given. The simulated result justifies this method.
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Martin R D, Schwartz S C. Robust detection of a known signal in nearly Gaussian noise. IEEE Trans. on IT, 1971, IT-17(1): 50-56.[2]刘有恒.信号检测与估计.北京:人民邮电出版社,1989:57-70,507-511.[3]Hinich J, Wilson G R. Detection of non-Gaussian signals in non-Gaussian noise using the bispectrum. IEEE Trans. on IT, 1990, IT-38(7): 1126-1131.[4]秦前清,杨宗凯.实用小波分析.西安:西安电子科技大学出版社,1994:54-64,87.[5]杨福生.小波变换的工程分析与应用.北京:科学出版社,1999:1-40,178-181.[6]朱华,黄辉宁,李永庆,梅文博.随机信号分析.北京:北京理工大学出版社,1990:282-286. ［7］孙山泽.非参数统计讲义.北京:北京大学出版社,2000:106-108.[7]崔景泰著,程正兴译.小波分析导论.西安:西安交通大学出版社,1995:333-335.[8]A.帕普里斯著,保铮等译.概率随机变量与随机过程.西安:西北电讯工程学院出版社,1984:212-244.[9]张贤达.时间序列分析-高阶统计量方法.北京:清华大学出版社,1996:25-46. -
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