摘要
首先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;其次,详细研究了利用小波包变换和随机共振来消除信号中夹杂的双模噪声。理论分析和仿真表明:此方法具有计算量小、算法比较简单和实时性较强的特点,不仅实现了将非高斯噪声——双模噪声转化为简单的高斯噪声来处理,而且比传统的高阶统计量的处理方法要优越。
On the basis of time-frequency analysis capabilities of multi-scale wavelet packet transform,this paper firstly studies statistics of one special of non-Gaussian noise that is bimodal noise.Then,wavelet packet and stochastic resonance to deal with bimodal noise are discussed.Theoretical analysis and simulation results show that this method has a small amount of calculation,simple algorithm and strong real-time characteristics.It not only transforms non-Gaussian noise(bimodal noise)into Gaussian noise,but also is better than the traditional higher-order statistics method.
出处
《河南科技大学学报（自然科学版）》
CAS
北大核心
2010年第5期35-39,共5页
Journal of Henan University of Science And Technology:Natural Science
基金
国家自然科学基金项目(60062001)
昌吉学院科研基金项目(2010YJYB009)
关键词
小波包变换
非高斯噪声
双模噪声
随机共振
Wavelet packet transform
Non-Gaussian noise
Dual-mode noise
Stochastic resonance
