含噪混合盲扰信分离中联合降噪技术研究

针对盲扰信分离技术在含噪混合条件下分离效果差的问题,文章采用经验模态分解和小波变换联合的降噪技术进行分离前的消噪预处理,研究了联合降噪的三种模式,分别对其降噪效果进行了仿真分析,得到了一种较好的联合降噪模式。将该模式与无噪环境下的盲分离算法相结合,弥补了经典盲源分离算法处理含噪混合盲扰信分离的不足。仿真结果表明该算法在一定范围的低信噪比条件下,能够从含噪的混合信号中恢复出通信信号源。     

基于Wigner-Ville分布及局部奇异值分解的磁记忆信号特征提取与识别

针对磁记忆检测中缺陷信号持续时间短且频率范围小的特点,为提取磁记忆信号的有效特征,根据矩阵奇异值的特点,提出一种基于Wigner-Ville分布及局部奇异值分解的磁记忆信号特征提取方法．通过将时频分布矩阵从时间轴和频率轴分别划分为不同局部矩阵,提取出各矩阵的奇异值来构造特征向量．然后,将构造的特征向量作为支持向量机的输入向量对不同检测区域的金属磁记忆信号进行识别．实验结果表明：基于Wigner—Ville分布及局部奇异值分解算法构造的特征向量能有效提取磁记忆信号的特征信息,提高支持向量机的识别精度．     

RDWT和NVF的自适应彩色图像水印算法

提出一种基于冗余小波(RDWT:Redundant Wavelet Transform)和噪声可见度函数(NVF:Noise Visibility Function)的彩色图像水印嵌入新算法,该算法利用主体图像的稳态广义Gaussian模型描述图像的局部特性,建立了水印信息的加权系数计算公式。在水印嵌入过程中先对主图像在YIQ空间的Y分量进行RDWT变换。同时利用NVF函数对经过加密变换的水印进行加权处理,然后利用奇异值分解将水印嵌入到变换域复杂纹理和边缘区域。实验结果表明该算法在保证水印不可见性的同时能很好地抵抗多种几何攻击和图像处理攻击,实现了水印鲁棒性、不可见性和容量的统一。     

基于agent的多传感器管理原型系统研究

近年来,基于agent的分布式智能系统已成功应用于众多领域。将多agent技术应用于多传感器管理领域研究,以开发多传感器智能管理的多agent系统,提出了其原型系统的基本框架和系统实现途径及方法,其中着重研究了融合agent与传感器agent的原型系统结构、基于多a-gent理论的传感器管理问题分布式任务分解与控制问题以及agent之间的协调合作问题。原型系统的研究,为实际应用系统的研制开发提供了理论指导和方法依据。     

非平稳数据处理方法与瞬时频率

利用“经验模式分解”(EMD)方法,任何复杂的数集都能够被分解为有限且通常数量较少的“本征模式函数”。“本征模式函数”产生瞬时频率,最终结果表示为H ilbert谱规定的能量-频率-时间分布。应用“经验模式分解”方法表示自然现象中的传统非线性平衡系统及其数据的数值结果,同时给出实例展示了这种新方法的作用和效果。这种方法阐明了能量-频率-时间分布,进一步显示出对非线性非平稳系统的处理效果———精确化、形象化和可视化。     

A novel signal feature extraction technology based on empirical wavelet transform and reverse dispersion entropy

Feature extraction is an important part of signal processing, which is significant for signal detection, classification, and recognition. The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields. Reverse dispersion entropy (RDE) proposed by us recently, as a nonlinear dynamic analysis method, has the advantages of fast computing speed and strong anti-noise ability, which is more suitable for measuring the complexity of signal than traditional permutation entropy (PE) and dispersion entropy (DE). Empirical wavelet transform (EWT), based on the theory of wavelet analysis, can decompose a complex non-stationary signal into a number of empirical wavelet functions (EWFs) with compact support set spectrum, which has better decomposition performance than empirical mode decomposition (EMD) and its improved algorithms. Considering the advantages of RDE and EWT, on the one hand, we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy; on the other hand, we use RDE as the features of EWFs to improve the signal separability and stability. Finally, we propose a novel signal feature extraction technology based on EWT and RDE in this paper. Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals. Moreover, it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.     

Recent progress on transition metal oxides and carbon-supported transition metal oxides as catalysts for thermal decomposition of ammonium perchlorate

As a main oxidizer in solid composite propellants, ammonium perchlorate (AP) plays an important role because its thermal decomposition behavior has a direct influence on the characteristic of solid com-posite propellants. To improve the performance of solid composite propellant, it is necessary to take measures to modify the thermal decomposition behavior of AP. In recent years, transition metal oxides and carbon-supported transition metal oxides have drawn considerable attention due to their extraor-dinary catalytic activity. In this review, we highlight strategies to enhance the thermal decomposition of AP by tuning morphology, varying the types of metal ion, and coupling with carbon analogue. The enhanced catalytic performance can be ascribed to synergistic effect, increased surface area, more exposed active sites, and accelerated electron transportation and so on. The mechanism of AP decom-position mixed with catalyst has also been briefly summarized. Finally, a conclusive outlook and possible research directions are suggested to address challenges such as lacking practical application in actual formulation of solid composite propellant and batch manufacturing.     

基于极化分解的目标识别方法研究

在全极化、高距离分辨力雷达体制背景下，研究了光学区雷达目标极化特性。利用极化分解将复杂目标分解为三个简单目标， 并提取描述三目标关系的特征参数对四类军用飞机目标进行了识别实验研究， 获得了良好的目标分类识别效果。     

一种新的二维谐波估计方法

研究了二维谐波信号相关矩阵后 ,提出了一种称之为“矩阵束的二维谐波估计 (MP2D)”算法 ,该算法既不需要求解二维特征多项式的根 ,也不需要在二维频率空间搜索谱峰 ,算法具有高效性。仿真实验表明 ,该算法在白噪声条件下对二维谐波频率估计具有高的精度和强的抗干扰能力。     

一类化学反应动力系统的定性分析

研究一类描述多分子化学反应的数学模型应用微分方程定性理论,完整地解决了该系统极限环的存在性、不存在性和唯一性问题。