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利用多尺度小波包变换良好的时频局部分析能力,对一类非高斯噪声——双模噪声的统计特性进行研究。经过实际计算及仿真比较,对于两种双模噪声模型,随着双模噪声序列长度的增加,双模噪声小波包子空间变换系数都将近似服从高斯分布。通过仿真,证实小波包检测系统的检测性能不仅跟输入双模噪声的模型无关,而且比传统的高阶统计量检测系统、经典检测系统的检测性能都要好。
The statistical properties of a class of non-Gaussian noise-dual-mode noise are studied by using the good time-frequency local analysis ability of multi-scale wavelet packet transform. After two-mode noise model and two-mode noise model, the spatial transform coefficients of the two-mode noise wavelet bunches will be approximately Gaussian distributed as the length of the dual-mode noise sequence increases. The simulation results show that the detection performance of the wavelet packet detection system is not only irrelevant to the input of the dual-mode noise model, but also better than the traditional high-order statistics detection system and the classical detection system.