Speech Encryption in Linear Canonical Transform Domain Based on Chaotic Dynamic Modulation

In order to transmit the speech information safely in the channel, a new speech encryption algorithm in linear canonical transform(LCT) domain based on dynamic modulation of chaotic system is proposed. The algorithm first uses a chaotic system to obtain the number of sampling points of the grouped encrypted signal. Then three chaotic systems are used to modulate the corresponding parameters of the LCT, and each group of transform parameters corresponds to a group of encrypted signals. Thus, each group of signals is transformed by LCT with different parameters. Finally, chaotic encryption is performed on the LCT domain spectrum of each group of signals, to realize the overall encryption of the speech signal. The experimental results show that the proposed algorithm is extremely sensitive to the keys and has a larger key space. Compared with the original signal, the waveform and LCT domain spectrum of obtained encrypted signal are distributed more uniformly and have less correlation, which can realize the safe transmission of speech signals.     

Research Progress on Discretization of Linear Canonical Transform

Linear canonical transformation(LCT) is a generalization of the Fourier transform and fractional Fourier transform. The recent research has shown that the LCT is widely used in signal processing and applied mathematics, and the discretization of the LCT becomes vital for the applications of LCT. Based on the development of discretization LCT, a review of important research progress and current situation is presented, which can help researchers to further understand the discretization of LCT and can promote its engineering application. Meanwhile, the connection among different discretization algorithms and the future research are given.     

基于线性正则变换的时频信号分离方法

时频信号分析是当今信号处理领域研究的一个热点问题,各种时频分布函数得到了广泛的研究和应用。线性正则变换是一种重要的时频分析工具。文中研究了线性正则变换与传统时频分布函数的关系;并基于这些关系,提出了一种新的时频信号分离方法,能够把在时频面上互不重叠、但在时域和频域均存在较强耦合的多分量合成信号有效地分离。仿真实例表明了该方法的正确性和实用性。     

Uncertainty Principle for the Quaternion Linear Canonical Transform in Terms of Covariance

An uncertainty principle(UP), which offers information about a signal and its Fourier transform in the time-frequency plane, is particularly powerful in mathematics, physics and signal processing community. Under the polar coordinate form of quaternion-valued signals, the UP of the two-sided quaternion linear canonical transform(QLCT) is strengthened in terms of covariance.The condition giving rise to the equal relation of the derived result is obtained as well. The novel UP with covariance can be regarded as one in a tighter form related to the QLCT. It states that the product of spreads of a quaternion-valued signal in the spatial domain and the QLCT domain is bounded by a larger lower bound.     

循环码最小距离几个下界的新证明

本文首先运用数字信号处理中的Z变换,证明周期序列线性复杂度与码字汉明重量间的关系,然后给出关于周期序列线性复杂度的几个定理,最后应用这些定理等,对循环码最小距离的几个下界作出新证明。     

一种基于余弦变换的LFM／CW测距系统信号处理方法

LFM／CW体制测距系统将目标距离信息转化为由回波信号与本振信号混频得到的差频信号的频率信息,通过分析该差频信号初始相位与目标距离的关系,研究了在测距中使用余弦变换代替傅里叶变换处理差频信号的可行性,分析了余弦变换引入的测距误差与系统参数间的关系,为减少处理差频信号时的运算量提供了理论参考。     

平稳小波变换在探地雷达资料降噪中的应用

小波变换方法是一种新的数学方法,具有强大的时频分析能力,广泛地应用到信号处理的各个领域。其中正交小波变换不具备线性相位、不具有平移不变性等特性,导致其在信号降噪领域仍存在很多问题,会使信号产生振荡现象。本文利用平稳小波变换对多组探地雷达模型实验与实际雷达资料的处理,说明该方法较好地保留了信号边缘细节,避免了伪Gibbs现象,其降噪效果明显优于普通正交小波方法的降噪效果。     

基于HHT的矢量传感器瞬态信号方位估计

针对瞬态信号存在时间短、变化快,传统的信号处理方法很难对其进行方位估计的问题,将希尔伯特-黄变换与矢量信号处理相结合应用到水声领域,提出了矢量希尔伯特-黄变换的方法.利用希尔伯特-黄变换获取信号的瞬态信息,结合矢量信号处理宽带方位估计提出了矢量瞬时方位估计的概念,在此基础上发展了矢量希尔伯特-黄变换水声应用的理论框架.海试表明新理论在瞬态信号处理和单矢量传感器目标方位估计方面,其性能比常规方法有了明显的提高.     

Computational uncertainty principle in nonlinear ordinary differential equations——Ⅱ.Theoretical analysis

The error propagation for general numerical method in ordinary differential equations ODEs is studied. Three kinds of convergence, theoretical, numerical and actual convergences, are presented. The various components of round-off error occurring in floating-point computation are fully detailed. By introducing a new kind of recurrent inequality, the classical error bounds for linear multi-step methods are essentially improved, and joining probabilistic theory the "normal" growth of accumulated round-off error is derived. Moreover, a unified estimate for the total error of general method is given. On the basis of these results, we rationally interpret the various phenomena found in the numerical experiments in part I of this paper and derive two universal relations which are independent of types of ODEs, initial values and numerical schemes and are consistent with the numerical results. Furthermore , we give the explicitly mathematical expression of the computational uncertainty principle and expound the i     

减小声音信号噪音干扰的处理方式的研究

研究能够减小声音信号中噪声成分的一种处理方式其原理基于模糊模式识别理论和信号的功率谱及其自相关函数互为博里叶变换对的理论．该方式可较好地达到减小噪声和防止子音失落的目的．     

Computational uncertainty principle in nonlinear ordinary differential equations

The error propagation for general numerical method in ordinary differential equations ODEs is studied. Three kinds of convergence, theoretical, numerical and actual convergences, are presented. The various components of round-off error occurring in floating-point computation are fully detailed. By introducing a new kind of recurrent inequality, the classical error bounds for linear multistep methods are essentially improved, and joining probabilistic theory the “normal” growth of accumulated round-off error is derived. Moreover, a unified estimate for the total error of general method is given. On the basis of these results, we rationally interpret the various phenomena found in the numerical experiments in part I of this paper and derive two universal relations which are independent of types of ODEs, initial values and numerical schemes and are consistent with the numerical results. Furthermore, we give the explicitly mathematical expression of the computational uncertainty principle and expound the intrinsic relation between two uncertainties which result from the inaccuracies of numerical method and calculating machine.     

指数分布对任意非负连续型随机变量的逼近

利用指数型分布类研究相依连续型非负随机变量序列的极限性质，得到一类强偏差定理，即用不等式表示的一类强极限定理，证明中提出了将似然比和Laplace变换应用于强极限定理研究的一种方法。     

基于LMI方法的线性广义系统非脆弱控制器设计

研究了线性广义系统的非脆弱控制器设计问题,目的是设计系统的非脆弱控制器;对控制器增益具有加法式摄动和乘法式摄动两种情形,应用线性矩阵不等式（LMI）方法分别给出了其状态反馈非脆弱控制器存在的线性矩阵不等式表示的充分条件,并用该不等式的解给出了非脆弱控制律的表达式;最后给出例子验证了所给方法的应用。     

一种计算时基失真估计不确定度的新方法

提出一种计算时基失真估计不确定度的新方法,讨论了时基失真估计过程中权值计算,理论推导以及仿真实验表明:只要谐波幅度比较小,多次谐波信号的方差都可以用含有基波方差来代替;给出了一种新的时基失真不确定度的定义以及一种实用的时基失真估计不确定度的计算方法.仿真实验验证了这个近似的估算公式的合理性以及可应用性.抖动方差以及加性噪声方差对时基失真估计的不确定度有一定的影响.     

Performance analysis of polarization space time cascade processing

Polarization-SpaceTime or SpaceTime-Polarization cascade processing can detect low velocity moving targets with polarized information on the received signal. To make a detailed analysis of the cascade processing, the adaptive weight is deduced. Then the detection performance against the cascade order, the space-time division and polarization division between the signal and clutter are qualitatively analysised, which would provide an instruction for choosing an appropriate cascade processing order. Simulation verifies the correctness of the analyzed conclusion.     

高精度数字化称重传感器系统研究

通过分析电源供电方式对测量精度的影响,采用间歇式恒流源对称重传感器供电,设计了基于滤波器和仪用放大器的信号调理电路,采用串行20位的模数转换器,按肖维勒准则剔除奇异数据,对数字化称重传感器系统进行优化.试验结果表明：高精度数字化称重传感器系统具有称重精度高、温度漂移小、灵敏度高的特点,为模拟称重信号的高精度数字化提供了一种解决方案.     

基于小波变换和时域融合的图像去噪方法

噪声对后续图像处理的质量有严重影响，经典的去噪方法在抑制噪声的同时会丢失图像中的细节。文中分析了信号与噪声在小波域的系数之间的关系。信号系数幅值较大．数量较少，而噪声系数幅值较小．数量较多；此外，利用从同源的多幅图像中抽取的信息能够比任何单一图像所提供信息更为准确可靠的时域融合技术，提出了一种基于小波变换和时域融合的去除噪声方法。实验证明这种方法能有效去除图像噪声，最大限度地保存图像细节。     

基于Wirtinger型积分不等式的线性时滞广义系统稳定性分析

针对线性时滞广义系统的稳定性问题,本研究通过适当的Lyapunov-Krasovskii泛函和Wirtinger型积分不等式方法,给出了新的时滞相关稳定的充分条件,并通过Matlab的LMI工具箱求解。数值算例表明,本文方法所获得的结果与自由权矩阵和时滞分割等方法相比,具有更小的保守性,说明本研究所获得的结果具有有效性和优越性。因此,该方法可以推广到区间时变时滞广义系统的稳定性研究和控制器设计中。     

时变时滞广义系统的时滞相关稳定性新判据

采用新型Lyapunov-Krasovskii增广泛函并引入积分不等式,结合凸组合的方法,研究了具有时变时滞广义系统的时滞相关稳定性问题,给出了基于线性矩阵不等式(LMI)的时滞相关稳定性新判据。数值例子表明,与文献[15]中的方法相比,本文结果可获得较大的允许时滞上界,数值例子验证了本文结果的有效性和优越性。