一类并行多步Runge－Kutta预校算法

一类并行多步Ｒｕｎｇｅ－Ｋｕｔｔａ预校算法李寿佛，甘四清（湘潭大学数学系）ＡＣＬＡＳＳＯＦＰＡＲＡＬＬＥＬＭＵＬＴＩＳＴＥＰＲＵＮＧＥ－ＫＵＴＴＡＰＲＥＤＩＣＴＯＲ－ＣＯＲＲＥＣＴＯＲＡＬＧＯＲＩＴＨＭＳ￥ＬｉＳｈｏｕ－ｆｏ；ＧａｎＳｉ－ｑｉｎｇ（Ｄ...     

两分块K－循环Toeplitz矩阵相乘的快速算法

两分块Ｋ－循环Ｔｏｅｐｌｉｔｚ矩阵相乘的快速算法余品能（南京工程兵工程学院）ＡＦＡＳＴＡＬＧＯＲＩＴＨＭＦＯＲＣＯＭＰＵＴＩＮＧＴＨＥＰＲＯＤＵＣＴＳＯＦＢＬＯＣＫＫ－ＣＩＲＣＵＬＡＮＴＴＯＥＰＬＩＴＺＭＡＴＲＩＣＥＳ￥ＹｕＰｉｎｎｅｎｇ（Ｉｎｓｔｉ...     

求解初值问题的仿真算法和人工舍入误差的应用

求解初值问题的仿真算法和人工舍入误差的应用李旺尧（中科院计算数学与科学工程计算所）ＯＮＳＩＭＵＬＡＴＩＯＮＡＬＧＯＲＩＴＨＭＳＦＯＲＩＮＩＴＩＡＬＶＡＬＵＥＰＲＯＢＬＥＭＳＡＮＤＡＰＰＬＩＣＡＴＩＯＮＯＦＡＲＴＩＦＩＣＩＡＬＲＯＵＮＤ－ＯＦＦＥＲＲＯ...     

解非线性最小二乘的并行连续极小化算法及其数值试验

解非线性最小二乘的并行连续极小化算法及其数值试验李庆扬，朱鹏（清华大学）ＡＰＡＲＡＬＬＥＬＣＯＮＴＩＮＵＯＵＳＭＩＮＩＭＩＺＡＴＩＯＮＡＬＧＯＲＩＴＨＭＦＯＲＳＯＬＶＩＮＧＮＯＮＬＩＮＥＡＲＬＥＡＳＴ－ＳＱＵＡＲＥＳＰＲＯＢＬＥＭＳＡＮＤＮＵＭＥＲＩ...     

双边障碍问题的迭代法

双边障碍问题的迭代法李董辉，曾金平（湖南大学应用数学系）ＩＴＥＲＡＴＩＶＥＳＯＬＵＴＩＯＮＦＯＲＴＷＯ－ＳＩＤＥＤＯＢＳＴＡＣＬＥＰＲＯＢＬＥＭＳ￥ＬｉＤｏｎｇ－ｈｕｉ；ＺｅｎｇＪｉｎ－ｐｉｎｇ（ＨｕｎａｎＵｎｉｖｅｒｓｉｔｙ）Ａｂｓｔｒａｃｔ：Ｉｎ...     

统计数据凑整问题的网络流算法

统计数据凑整问题的网络流算法金大勇，杨承恩（长沙铁道学院）ＮＥＴＷＯＲＫＡＬＧＯＲＩＴＨＭＳＦＯＲＴＨＥＤＡＴＡＲＯＵＮＤＩＮＧＰＲＯＢＬＥＭ￥ＪｉｎＤａ－ｙｏｎｇ；ＹａｎｇＣｈｅｎｇ－ｅｎ（ＣｈａｎｇｓｈａＲａｉｌｗａｙＩｎｓｔｉｔｕｔｅ）Ａｂｓｔ...     

解大型稀疏线性代数方程组的预条件Krylov子空间方法

解大型稀疏线性代数方程组的预条件Ｋｒｙｌｏｖ子空间方法邓健新（中国科学院计算中心）ＰＲＥＣＯＮＤＩＴＩＯＮＩＮＧＫＲＹＬＯＶＳＵＢＳＰＡＣＥＭＥＴＨＯＤＳＦＯＲＬＡＲＧＥＳＰＡＲＳＥＬＩＮＥＡＲＡＬＧＥＢＲＡＩＣＳＹＳＴＥＭＳ￥ＤｅｎｇＪｉａｎ－ｘｉ...     

求解非线性矩阵特征值问题的一个三阶收敛的算法

求解非线性矩阵特征值问题的一个三阶收敛的算法陈广义，薛彦才（中国科学院沈阳计算所）ＡＣＵＢＩＣＡＬＬＹＣＯＮＶＥＲＧＥＮＴＡＬＧＯＲＩＴＨＭＦＯＲＳＯＬＶＩＮＧＮＯＮＬＩＮＥＡＲＥＩＧＥＮＶＡＬＵＥＰＲＯＢＬＥＭＳ￥ＣｈｅｎＧｕａｎｇ－ｙｉ；ＸｕｅＹ...     

一种产品数据的图形表达方法──EXPRESS-G

一、概述国际标准化组织制定的标准ＩＳＯ１０３０３产品数据的表达与交换是当前在ＣＡＤ领域中的重要的数据交换标准,标准的第１１部分是进行产品建模的基础：ＥＸＰＲＥＳＳ语言参考手册。在参考手册中提出了一种与ＥＸＰＲＥＳＳ语言相对应的产品模型图形描述方法：ＥＸＰＲＥＳＳ－Ｇ,在标准中称为“ＥＸＰＲＥＳＳ语言的图形子集”。该表达方法支持ＥＸＰＲＥＳＳ语言的一个子集。ＥＸＰＲＥＳＳ—Ｇ的特点是用图形的方法描述概念和概念之间的关系,所以它对于理解用ＥＸＰＲＥＳＳ语言写出的数据模型有非常大的帮助。这个方法自成体…     

抛物型微分方程组初边值问题的有限元算法

抛物型微分方程组初边值问题的有限元算法王同科（河南师范大学数学系）ＦＩＮＩＴＥＥＬＥＭＥＮＴＭＥＴＨＯＤＦＯＲＰＡＲＡＢＯＬＩＣＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＷＩＴＨＩＮＩＴＩＡＬＡＮＤＢＯＵＮＤＡＲＹＶＡＬＵＥＰＲＯＢＬＥＭＳ￥Ｗａｎｇ...     

Parameter estimation of the 2D‐GTD model and RCS reconstruction based on an improved 2D‐ESPRIT algorithm

The two‐dimensional estimating signal parameter via rotational invariance techniques (2D‐ESPRIT) algorithm is a classical method to estimate parameters of the two‐dimensional geometric theory of diffraction (2D‐GTD) model. While as signal‐to‐noise‐ratio (SNR) decreases, the parameter estimation performance of 2D‐ESPRIT algorithm is severely influenced. To solve this problem, a performance‐enhanced 2D‐ESPRIT algorithm is proposed in this article. The improved 2D‐ESPRIT algorithm combines the conjugate data with the original back‐scattered data and obtains a novel covariance matrix by squaring the original total covariance matrix. Simulation results indicate that the improved algorithm has a better noise robustness and a more stable parameter estimation performance than the classical ESPRIT algorithm and the classical TLS‐2D‐ESPRIT algorithm. To further validate the superiority of the improved 2D‐ESPRIT algorithm, reconstructed radar cross section (RCS) is presented in this article. Compared with the classical 2D‐ESPRIT algorithm, the proposed algorithm presents higher RCS fitting precision. Furthermore, the impacts of other factors on parameter estimation, such as matrix pencil parameters and paring parameters, are also studied in this article.     

Underwater sources location in non-Gaussian impulsive noise environments

The class of alpha-stable distributions is better for modeling impulsive noise than Gaussian distribution in array signal processing. After briefly introducing the statistical characteristics of stable distribution and the fractional lower order statistics, including the covariation and the fractional order correlation, this paper proposes a new FOC-ESPRIT method of 2-D direction finding based on the fractional order correlation and subspace technique for underwater 2-D source localization using a vector hydrophones array under alpha-stable noise conditions. A vector hydrophone comprises two or three spatially co-located, orthogonally oriented identical velocity hydrophones (each of which measures one Cartesian component of the underwater acoustical particle velocity vector-field) plus an optional pressure hydrophone. Simulation experiments show that the proposed method is robust in a wide range of characteristic exponent values of stable distribution. Its performances are better than those of the conventional second-order statistics based ESPRIT algorithm, furthermore, the fractional order correlation is more suitable than the covariation in practical applications.     

色噪声环境下双基地MIMO雷达相干目标角度估计算法

通过研究多输入多输出(Multiple input and multiple out,MIMO)雷达的角度估计算法,针对色噪声环境下双基地MIMO雷达相干目标角度估计问题,基于双基地MIMO雷达的信号模型,利用MIMO雷达的接收数据,通过四阶累积量的计算消除了色噪声的影响,并证明得到的一组矢量包含所有目标的角度信息;然后利用得到的四阶累积量矢量构造出块Hankel矩阵,并证明该矩阵的秩等于目标总数,且不受信号相干性的影响,通过奇异值分解,结合ESPRIT算法实现了色噪声环境下对相干目标的角度估计.算法结合四阶累积量和MIMO雷达的估计性能,具有自动抑制加性高斯白噪声和色噪声的能力,实现了相干目标的有效估计和参数的自动配对,提高了抗噪能力,更利于在实际中应用.最后计算机仿真结果证实了算法的有效性和可行性.     

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.     

Comparison of total least squares and instrumental variable methods for parameter estimation of transfer function models

The estimation of the parameters of a transfer function model is considered. Relationships between the total least squares (TLS) and instrumental variable (IV) approaches are outlined. Both methods are able to compute strongly consistent parameter estimates. TLS can be considered as a variation on the IV method where the IV are functions of the time instant and the estimated model parameters. TLS computes strongly consistent estimates of the true model parameters if the outputs and possibly the inputs are independently disturbed by discrete, stationary white noise with zero mean and equal variance. The IV need not be generated. Hence TLS is much simpler to use but more restrictive (IV allows arbitrary noise models) and computationally not so attractive. Next, simulation results are presented comparing the short sample accuracy properties of both methods. When the outputs and possibly the inputs are disturbed by stationary zero mean while noise, TLS outperforms the ordinary IV methods. The accuracy becomes comparable by extending the IV sufficiently. The superiority of TLS is particularly clear in cases where the zeros of the polynomial operating on the outputs are close to the unit circle or where both the inputs and outputs are noisy.     

一类高分辨方位估计算法的稳健性研究

在水下多目标方位估计中,为了降低阵列误差对高分辨方位估计算法性能的影响,增强算法的稳健性,提出通道归一Toeplitz化的误差校正方法,通过计算机仿真对MUSIC、Mini-Norm、Root-MUSIC、TLS-ESPRIT和MODE算法性能的分析研究,结果表明此校正方法能很好地改善高分辨算法的性能,并且水池实验数据的处理结果也进一步验证了仿真结论的正确性;而且从仿真和水池实验结果可以看到经校正后TLS-ESPRIT、Root-MUSIC和MODE算法稳健性高,有较低的噪声分辨门限,工程应用前景良好.     

一种附加约束的ESPRIT测向方法

经典旋转不变技术（ESPRIT）算法测向估计性能在大多理论情况下接近于克拉美罗下界,且其在计算量方面要明显优于多信号分类算法（MUSIC）。本文首先论述了经典ESPRIT方法,描述了广义特征值分布在单位圆附近的实际工程应用情况,并提出了一种将广义特征值附加约束在单位圆上的修正ESPRIT算法。理论分析和仿真实验表明,该算法同经典的ESPRIT算法相比,当阵列存在几何误差的情况下,可明显改善测向估计的性能。     

估计相干与非相干信源的ESPRIT方法研究

在目前信号波达方向（Direction-Of-Arrival,DOA）估计中,常规ESPRIT算法是一种速度快、精度高的常用算法,但对于低信噪比下混合信号（同时含有相干与非相干信号）,常规ESPRIT算法难以估计出它们的DOA。结合解相干MUSIC和常规ESPRIT算法的优点,提出了一种新的估计相干与非相干信源的ESPRIT方法,新方法充分利用数据协方差矩阵的自相关和互相关信息来重构含有信号方位数据的新矩阵,再从它的特征值中解得信号的到达角。计算机仿真结果验证该方法在混合信号估计中的优越性和可靠性。     

基于ESPRIT的噪声抑制频率估计算法

在中低信噪比时,协方差矩阵受噪声影响较大导致ESPRIT算法性能降低,使其与克拉美罗下限(CRLB)有一定距离。针对该问题,提出一种基于ESPRIT的噪声抑制频率估计算法,利用信号频域内若干子带的谱线估计协方差矩阵,通过该矩阵的特征向量张成信号子空间,估计信号各分量的频率。实验结果表明,该算法能用于多个频率分量的信号分析,归一化频率估计的范围为 ,且性能接近于CRLB下限。     

基于不同背景噪声的联合检测技术

提出一种简单、实用的联合检测技术,将经典的基于能量和过零率的双门限法与基于小波变换的子带能量法巧妙地结合起来进行语音信号的端点检测,充分利用双门限法算法简单、实时性好、准确率高,小波子带能量对高斯白噪声区分性能强的特性。仿真结果表明新算法能提高检测系统在噪声环境下端点检测的准确率。