重叠与正交脉冲信号下的UWB系统性能研究

介绍了TH-UWB信号模型,推导出了在AWGN信道条件和多径条件下,重叠和正交脉冲信号下的TH-BPPMUWB系统的误码率公式,并进行了仿真。仿真结果表明在AWGN信道条件下,基于重叠脉冲信号的TH-BPPM系统性能优于基于正交脉冲信号的TH-BPPM;多径条件下的正交TH-BPPM的系统性能优于AWGN信道条件下的系统性能。     

一种基于小波变换的红外导引头信号检测方法

针对某型号红外导引头信号的检测问题,提出了一种基于离散平稳小波变换的微弱脉冲信号检测方法.根据有用脉冲信号与噪声信号在频谱特性上的差异,对导引头信号进行多尺度的离散平稳小波变换,利用分解后得到的低频近似信号逼近信号中的低频噪声来滤出低频噪声的干扰,同时采用阈值去噪的方法处理信号中的白噪声.将该方法应用于仿真信号和真实导引头信号检测,仿真实验结果表明:该方法在有效克服传统离散正交小波变换去噪时容易产生的Gibbs现象的前提下,极大地提高了导引头信号的信噪比,增强了导引头的探测能力.     

对脉冲耦合神经网络中被动神经元的脉冲周期分析

本文研究了离散PCNN中被动神经元的被动脉冲周期,首先定义了动态比较比,而不是逻辑比较来描述神经内状态与动态阈值之间的线性差异。然后利用动态比较比的最大下限,给出了一个近似准确的被动脉冲周期公式,并通过对估计和实际被动脉冲周期的误差分析,证明了该公式的合理性。此外,我们从估计的脉冲周期中推导出一个稳定的脉冲周期,从而使神经元可以连续地在两个不同的时间阶段进行非周期性和周期性的脉冲。此外,还估算了被动神经元开始周期性脉冲的初始阶段,并举例说明,结果与理论分析一致。     

时滞系统控制问题块脉冲算子解的收敛性

本文给出了一种基于块脉冲算子的离散逼近格式.应用这种逼近格式,可以获得时滞非 线性最优控制问题的块脉冲级数解.本文证明了这种块脉冲级数解将收敛于这类问题的精 确解,并具有一阶收敛速度.     

参数不确定离散混沌系统的模糊脉冲控制

研究了参数不确定离散混沌系统的控制问题.通过Takagi-Sugeno(TS)模糊动态模型和脉冲控制技术,建立了参数不确定离散混沌系统的Takagi-Sugeno模糊脉冲控制模型,然后利用矩阵分析和Lyapunov稳定性理论,得到了参数不确定离散混沌系统控制的一个充分条件,最后通过实例证实了该结果的正确性,相比传统的控制方法,基于Takagi-Sugeno模型的模糊脉冲控制方法具有一定的优越性.     

基于正交镜像滤波器组的子带脉冲压缩方法

针对超宽带雷达频带分割滤波器不理想、导致子带脉冲压缩和直接脉冲压缩结果相差较大的问题,本文提出了基于正交镜像滤波器组的子带脉冲压缩方法。首先设计了近似完全重建的正交镜像滤波器组,定义目标函数为通带误差、阻带能量和失真转移函数平方误差的加权和,通过无约束的变尺度方法将其最小化,然后用设计的正交镜像滤波器作为频带分割滤波器,实现子带脉冲压缩。仿真结果表明,本文设计的正交镜像滤波器组,相比现有的设计,具有更小的峰值重建误差、通带和阻带误差。提出的子带脉冲压缩方法,与传统方法相比,主副瓣比和主瓣宽度等脉压性能也明显提高。     

方波脉冲变换及其应用

方波脉冲函数是一类新型的正交函数,它可在工程技术领域中得到广泛的应用。由于这种函数具有简明的定义、独特的运算性质、灵活的处理,不仅使人易于掌握,而且具有推导简明、公式简单、计算容易、快捷、准确度高,配合计算机使用,易于编程序、省时和节省计算机内存等一系列优点。有兴趣者,可参考文献[3]。     

基于两变量Krawtchouk矩的图像重建

传统的离散正交Krawtchouk矩的基函数由两个单变量的Krawtchouk多项式乘积构成,它割裂平面两个方向之间的联系。提出了一种新的、以两变量Krawtchouk正交多项式为基函数的图像矩,并推导了正则化后两变量多项式的简单的计算方法。重建实验结果表明,相对于同系数的单变量的离散正交矩,两变量离散正交矩的重建误差更小。     

一类离散模糊系统的迭代学习控制算法

针对离散T-S模糊系统的终端控制问题,提出了一种基于离散Legendre正交多项式的迭代学习算法。该算法把待求控制量表示为离散Legendre正交多项式的线性组合,将求控制量问题转化为求离散Legendre正交多项式系数问题。在此基础上,用迭代学习的方式来修正控制量的离散Legendre系数,并运用不确定离散系统的H∞设计方法求解学习增益矩阵。最后以机器人为例进行仿真,仿真结果表明了所提算法能实现工业机器人的精确定位。     

基于三维离散余弦变换的彩色图象压缩编码

离散余弦变换对图象信号有近似最优的去相关能力，但多维的变换公式一直没有给出，为此深入研究了三维离散余弦变换，提出了任意尺寸的三维函数f(x,y,z)的正交离散余弦变换公式，克服了以前系数的取值必须相等的缺点，并将之应用于彩色静止图象的压缩编码中，使得彩色图象的R，G，B3帧可以作为一个整体同时进行变换，极大地去除了图象R，G，B3帧间的相关性，理论分析和实验结果表明，在大幅度地增加压缩比的同时，峰峰信噪比也有明显提高，并且与国际标准JPEG，MPEG有很好的兼容性。     

Discrete pulse orthogonal functions for the analysis,parameter estimation and optimal control of linear time-varying digital systems

The analysis, parameter estimation and optimal control of linear time-varying digital systems are facilitated in this study. The discrete pulse orthogonal functions (DPOFs) and their operational matrices are taken as a sharp tool. The applications of DPOFs to digital control systems are analogous to those of the known block pulse functions (BPFs) in continuous systems. By applying the DPOFs, approximate solutions of digital time-varying systems can easily be obtained by convenient algorithms. Three examples are illustrated to demonstrate the proposed DPOF technique, and the approximate results are very accurate and satisfactory.     

Research on the Approach to Assess Missile Operational Effectiveness Based on OPN

Object Petri Net （OPN） which combines Petri net with object-oriented theory gives an effective method to use the Petri net in the field of M＆S of Discrete Event Dynamic System. The concept and mechanism of object is brought in, and ttie function of ba- sic Petri net is expanded. It is a new idea to apply OPN to missile operational effectiveness assessment system. The expanded func- tion of OPN is helpful for M＆S of discrete missile combat system. Since kinds of stochastic factors of the combat are considered in the simulation, the assessment of operational effectiveness has high reliability. The structure and the combat process of ICBM combat system are studied, and then the framework of OPN-based missile operational effectiveness assessment system and its operational mechanism are given.     

摄动离散矩阵Lyapunov方程解的估计

研究摄动离散矩阵Lyapunov方程解的估计问题,利用矩阵运算性质及Lyapunov稳定性理论,给出在结构不确定性假设下方程解的存在条件及解的上下界估计,估计结果由一个线性矩阵不等式(LMI)和两个矩阵代数Riccati方程确定．针对几种不确定性假设,进一步给出矩阵代数Riccati方程的具体形式．最后通过一个算例说明了所得结果的有效性．     

Dissipative interval observer design for discrete‐time nonlinear systems

This paper studies the problem of designing interval observers for a family of discrete‐time nonlinear systems subject to parametric uncertainties and external disturbances. The design approach states that the interval observers are constituted by a couple of preserving order observers, one providing an upper estimation of the state while the other provides a lower one. The design aim is to apply the cooperative and dissipative properties to the discrete‐time estimation error dynamics in order to guarantee that the upper and lower estimations are always above and below the true state trajectory for all times, while both estimations asymptotically converge towards a neighborhood of the true state values. The approach represents an extension to the original method proposed by the authors, which focuses on the continuous‐time nonlinear systems. In some situations, the design conditions can be formulated as bilinear matrix inequalities (BMIs) and/or linear matrix inequalities (LMIs). Two simulation examples are provided to show the effectiveness of the design approach.     

基于观测器的2-D奇异系统Roesser模型的H∞滤波

This paper discusses the problem of the H∞ filtering for discrete time 2-D singular Roesser models (2-D SRM). The purpose is to design an observer-based 2-D singular filter such that the error system is acceptable, jump modes free and stable, and satisfies a pre-specified H∞ performance level. By general Riccati inequality and bilinear matrix inequalities (BMI), a sufficient condition for the solvability of the observer-based H∞ filtering problem for 2-D SRM is given. A numerical example is provided to demonstrate the applicability of the proposed approach. Key words 2-D singular systems, jump modes, general Riccati inequality, bilinear matrix i     

Hybrid extended Fourier series for optimal control of nonlinear algebraic dynamical systems

The paper introduces a new method for finding optimal control of algebraic dynamic systems. The structure of algebraic dynamical systems is nonlinear with quadratic and bilinear terms. A new hybrid extended Fourier series is introduced, and state and control variables of the system are expanded by this series. Moreover, properties of new series are presented, and integration and product operational matrices are obtained. Using operational matrices, optimal control of the systems is converted to a set of simultaneous nonlinear algebraic relations. An illustrative example is included to compare our results with those in the literature.     

Analysis of linear time-varying systems and bilinear systems via Taylor series

Linear time-varying systems and bilinear systems are each analysed via Taylor series. Using the operational matrix for integration and the product operational matrix, the dynamical equation of a linear time-varying system (or a bilinear system) is reduced to a set of simultaneous linear algebraic equations. The coefficient vectors of the Taylor series expansions can be determined recursively by the algorithm derived. The algorithm proposed here is similar to those already developed for orthogonal functions; however, owing to the simplicity of the operational matrix of integration and the product operational matrix, Taylor series present considerable computational advantages compared with the other polynomial series, provided that both the input and the output signals are analytic functions of t.     

Parameter identification of distributed parameter systems in the presence of measurement noise

A new approach to recursive parameter identification of second-order distributed parameter systems in the presence of measurement noise under unknown initial and boundary conditions is proposed. A two-dimensional low-pass filter is introduced to pre-filter the observed data corrupted by measurement noise. The low-pass filter is designed in the continuous time-space domain and discretized by bilinear transformation. Thus a discrete estimation model of the system under study is easily constructed with filtered input-output data for recursive identification algorithms. The recursive least squares method is still efficient in the presence of low measurement noise if the filter parameters are designed so that the noise effects are reduced sufficiently. Using filtered input data as instrumental variables, a recursive instrumental variable method is also presented to obtain consistent estimates when the digital low-pass filters are not designed successfully or when the output data is corrupted by high measurement noise. Illustrative examples are given to demonstrate the applicability of the proposed methods.     

基于Krein空间的线性离散时变系统H∞故障估计

研究一类受L2范数有界未知输入影响的线性离散时变系统H∞故障估计问题. 首先将系统H∞故障估计归结为二次型最小化问题, 然后引入相应的Krein空间系统, 应用Krein空间Kalman滤波理论, 推导并证明H∞故障估计问题可解的充要条件, 给出基于矩阵Riccati方程的H∞故障估计器设计, 为故障估计问题提供新的理论方法, 并通过算例验证本文提出方法的有效性.     

Analysis of linear time-varying systems and bilinear systems via shifted Chebyshev polynomials of the second kind

Linear time-varying systems and bilinear systems are analysed via shifted Chebyshev polynomials of the second kind. Using the operational matrix for integration and the product operational matrix, the dynamical equation of a linear time-varying system (or bilinear system) is reduced to a set of simultaneous linear algebraic equations. The coefficient vectors of shifted Chebyshev polynomials of the second kind can be determined by using the least-squares method. Illustrative examples show that shifted Chebyshev polynomials of the second kind having a finite number of terms are more accurate than either the Legendre or Laguerre methods.