【作者】 查代奉；

【导师】 邱天爽；

【作者基本信息】 大连理工大学 ， 信号与信息处理， 2006， 博士

【摘要】 本论文在简要介绍稳定分布统计特性的基础上,讨论了一种不同于二阶过程功率谱密度的共变谱密度概念,建立了一种基于自共变序列与共变谱密度的非高斯稳定分布白噪声的概念及其判断标准,对传统意义上的白噪声概念进行了广义化。依据稳定分布的参数模型,论述了一种基于α谱的频域广义白化滤波方法,并分析了一种新的预测反卷积白化系统中的广义尤拉-沃克(GYW)方程白化滤波器模型。本论文还依据已有的多项式自回归(PAR)模型,讨论了非线性稳定分布有色噪声概念并建立其非线性PAR模型,提出了EIRLP算法对非线性稳定有色噪声的模型参数进行估计。本论文还讨论了一种分数极点系统中稳定分布有色噪声的白化逆滤波方法,并分析了算法的长记忆、最小相位、收敛特性。 在自适应滤波方面,本文基于SαSG分布噪声模型,讨论了自适应混合矩滤波的修正RMN(M-RMN)算法,并对M-RMN算法进行了步长归一化改进。提出了基于滑动窗与韧性M函数的自适应韧性广义递归最小p范数(R-SW-RLP)滤波算法,并对算法的渐进特性进行了分析。讨论了基于新息过程最小p范数准则的递归Kalman(LP-Kalman)滤波算法,并分析了它与递归最小p范数(RLP)滤波算法的关系,进行了算法的韧性改进与渐近特性分析。此外,本文还讨论了稳定分布白噪声环境下的基于中值正交化准则的滤波算法、基于最小平均p范数准则的格型滤波器及其递归实现、基于最小误差熵准则的滤波方法。 在阵列信号处理方面,依据泄漏梯度下降原理、矩阵对角加载方法通过对现有的最小平均p范数(LMP)波束形成方法加以改进,提出了新的广义最小平均p范数(GLMP)波束形成方法。利用分数低阶协方差(FLOC)推导了基于分数低阶协方差矩阵的波束形成方法,并分析了该波束形成器的旁瓣特性。对传统的最小范数(Min-Norm)方向估计算法进行改造,讨论了一种基于分数阶相关(FOC)的方向估计新方法。本文还利用已有的矢量水听器模型建立了一种水下二维定位系统,提出了一种基于分数阶相关(FOC)的水下二维定位算法。 论文还介绍了稳定分布噪声特征函数的玻耳测度表示及玻耳测度的估计方法,利用玻耳测度的峰值确定混合矩阵的基矢量个数,从而可以确定各个独立分量。讨论了基于分数低阶统计量(FLOS)的盲信号源分离网络结构与预白化过程,并利用一种新型传递函数修正了分离算法。在应用方面,论文还探讨了基于最小分散系数(MD)准则与旋转变换的诱发电位(EP)信号分离提取算法。更多还原

【Abstract】 This dissertation briefly introduces the statistical characteristics of stable distribution and proposes a new spectral density different from power spectrum density of second order processes. Thus a new concept of stable white noise and a method of whitening based on covariation sequence and the fractional order spectrum--covariation spectrum under alpha-stable conditions are obtained. According to parameter model of stable distribution, we discuss a new frequency domain whitening method based on alpha spectrum. Methods of whitening based on generalized Yuler-Walker equation and prediction deconvolution and PAR nonlinear model are also get.A new adaptive mixed moments filtering algorithm and a new adaptive generalized recursive least p-norm filtering algorithm based on SaSG noise model are obtained. This dissertation discusses a new adaptive generalized recursive least p-norm Kalman filtering algorithm based on innovation process with infinite variances and improves and analyzes its robustness and performances. A new adaptive filtering algorithm based on median orthogonality criterion and adaptive recursive least mean p-norm lattice filtering algorithm and a new adaptive filtering algorithm based on minimum error entropy criterion are also discussed.This dissertation discusses a new generalized least mean p-norm beamforming method based on the matrix diagonal loading and the leakage iteration. What’s more, a new beamforming method based on the fractional lower order covariance matrix under alpha-stable interference conditions is analyzed. Furthermore, a new method of DOA estimation based on the fractional order correlation is discussed. The dissertation also discusses a new method of 2-D direction finding for underwater 2-D source localization using a vector hydrophones array under alpha-stable noise conditions.Identifying algorithm of the independent components of an alpha-stable random vector for under-determined mixtures is discussed and the method is based on an estimate of the discrete spectral measure for the characteristic function of an alpha-stable random vector. The dissertation proposes neural network structures related to multilayer feed-forward networks for performing BSS based on fractional lower order statistics and subspace technique. This a new EP estimation algorithm based on minimum dispersion (MD) criterion and Givens matrix is obtained.This dissertation uses shot noise to model the speckle noise, analyzes and modeled the coefficients of 2-D multi-resolution wavelet decomposition of logarithmically transformed images using alpha stable distribution. Consequently, we obtain a new function of classifying the coefficients and a new noise-removal method based on multi-resolution wavelet decomposition and alpha stable model.更多还原