动力系统时间延迟重构变换的行为

利用延迟重构变换的雅可比行列式，分析了动力系统重构中的拓朴性质。讨论了延迟时间的选择和重构变量本身的条件稳定性对重构拓朴的影响。利用条件Ｌｙａｐｕｎｏｖ指数分析了重构变量本身的好坏。

面向卫星通信的K波段低剖面可重构线圆极化变换表面

针对K波段卫星通信容量大、工作模式灵活的需求,设计了一款用于K波段卫星通信的反射型可重构线圆极化变换表面。该线圆极化变换表面基于改进型耶路撒冷十字结构,在PIN二极管导通和关闭时,分别可在18.59~20.50 GHz和18.66~23.19 GHz实现线极化波转右旋圆极化波和左旋圆极化波,重叠工作频段为18.66~20.50 GHz,带宽1.84 GHz。该极化变换表面的单元尺寸为0.22λ×0.2λ×0.083λ(λ为重叠频段中心工作波长),剖面高度仅为0.083λ。该极化变换表面在PIN二极管处于导通和关闭状态下,入射角度稳定性分别为40°和20°,且交叉极化电平低于-60 dB。

考虑变换域融合方法的刀具磨损区域三维重构

针对数控机床加工领域刀具磨损区域的三维重构精度提高的问题,提出了变换域融合方法。将非下采样轮廓波变换和小波变换相结合,对非下采样轮廓波变换得到的低频系数采用小波变换方法进行融合,对得到的高频系数构造区域方差进行融合,突出刀具磨损图像的整体灰度信息和边缘细节信息,从而获得更为清晰的二维刀具图像,以及更为准确的磨痕形貌及磨痕体积。对基于非下采样轮廓波变换、小波变换方法和变换域融合方法得到磨损区域三维形貌和磨损体积与显微镜的观察结果进行了对比分析,发现提出的方法得到的三维形貌与显微镜结果最接近,且计算出的磨损体积平均相对误差小于10%。分析和实验数据表明,所提方法无论在图像的清晰度和磨损体积的准确性方面都有一定的优势,该方法对于刀具磨损区域三维重构精度较高,优于单独采用非下采样轮廓波变换和小波变换方法得到的结果。

虚拟式小波变换信号分析仪的设计及应用

介绍了一种新型的适于工程信号分析的虚拟式小波变换信号分析仪的设计。该虚拟仪器不仅集成了以小波变换为核心的信号分解和信号重构等主要功能，而且还包括了FFT、细化分析、时域统计分析、相关分析等一些辅助功能。结合虚拟仪器技术，充分利用计算机的资源。该仪器具有几大优点：友好的用户界面、快速的小波变换算法、丰富的分析功能、极高的性价比。文中给出了几个实际应用例子。

Reconfigurable implementation of AES algorithm IP core based on pipeline structure

In order to improve the data throughput of the advanced encryption standard （AES） IP core while reducing the hardware resource consumption and finally achieving a tradeoff between speed and area, a mixed pipeline architecture and reconfigurable technology for the design and implementation of the AES IP core is proposed. The encryption and decryption processes of the AES algorithm are achieved in the same process within the mixed pipeline structure. According to the finite field characterizations, the Sbox in the AES algorithm is optimized. ShiftRow and MixColumn, which are the main components in AES round transformation, are optimized with the reconfigurable technology. The design is implemented on the Xilinx Virtex2p xc2vp20-7 field programmable gate array （FPGA） device. It can achieve a data throughput above 2.58 Gbit/s, and it only requires 3 233 slices. Compared with other related designs of AES IP cores on the same device, the proposed design can achieve a tradeoff between speed and area, and obtain satisfactory results in both data throughput and hardware resource consumption.

改进小波结合BP网络的风力发电机故障诊断

针对风力发电机早期故障时定子电流特征量难以提取的问题,提出了单子带重构改进小波变换结合BP神经网络的风力发电机故障诊断新方法。通过对风力发电机的定子电流进行单子带重构改进小波变换,消除了传统小波变换中的频率混叠现象;从小波变换后的子带信号中选取特征域、提取特征量作为BP神经网络的输入;在此基础上,结合BP神经网络的输入输出非线性映射能力,完成对故障的诊断和定位。经过仿真实验证实,该方法准确地实现了对风力发电机故障的诊断。

A fast-convergence POCS seismic denoising and reconstruction method

The efficiency, precision, and denoising capabilities of reconstruction algorithms are critical to seismic data processing. Based on the Fourier-domain projection onto convex sets （POCS） algorithm, we propose an inversely proportional threshold model that defines the optimum threshold, in which the descent rate is larger than in the exponential threshold in the large-coefficient section and slower than in the exponential threshold in the small-coefficient section. Thus, the computation efficiency of the POCS seismic reconstruction greatly improves without affecting the reconstructed precision of weak reflections. To improve the flexibility of the inversely proportional threshold, we obtain the optimal threshold by using an adjustable dependent variable in the denominator of the inversely proportional threshold model. For random noise attenuation by completing the missing traces in seismic data reconstruction, we present a weighted reinsertion strategy based on the data-driven model that can be obtained by using the percentage of the data-driven threshold in each iteration in the threshold section. We apply the proposed POCS reconstruction method to 3D synthetic and field data. The results suggest that the inversely proportional threshold model improves the computational efficiency and precision compared with the traditional threshold models; furthermore, the proposed reinserting weight strategy increases the SNR of the reconstructed data.

一种基于小波阈值函数的交通图像去噪算法

针对高速运动条件下交通实时监测图像的失真和去噪问题,介绍小波阈值图像去噪过程和传统GCV阈值的原理,引入整数小波变换和合并递推运算的思想,提出一种快速递推GCV阈值的小波图像去噪方法。仿真实验分析了传统GCV阈值和快速递推GCV阈值去噪的效果,并比较了两种算法的复杂度。结果表明,快速递推GCV阈值算法不仅保留了传统GCV阈值算法去噪效果明显的特点,而且很好地解决了算法复杂度较高的问题,具有良好的应用前景。

Bernoulli-based random undersampling schemes for 2D seismic data regularization

Seismic data regularization is an important preprocessing step in seismic signal processing. Traditional seismic acquisition methods follow the Shannon–Nyquist sampling theorem, whereas compressive sensing（CS） provides a fundamentally new paradigm to overcome limitations in data acquisition. Besides the sparse representation of seismic signal in some transform domain and the 1-norm reconstruction algorithm, the seismic data regularization quality of CS-based techniques strongly depends on random undersampling schemes. For 2D seismic data, discrete uniform-based methods have been investigated, where some seismic traces are randomly sampled with an equal probability. However, in theory and practice, some seismic traces with different probability are required to be sampled for satisfying the assumptions in CS. Therefore, designing new undersampling schemes is imperative. We propose a Bernoulli-based random undersampling scheme and its jittered version to determine the regular traces that are randomly sampled with different probability, while both schemes comply with the Bernoulli process distribution. We performed experiments using the Fourier and curvelet transforms and the spectral projected gradient reconstruction algorithm for 1-norm（SPGL1）, and ten different random seeds. According to the signal-to-noise ratio（SNR） between the original and reconstructed seismic data, the detailed experimental results from 2D numerical and physical simulation data show that the proposed novel schemes perform overall better than the discrete uniform schemes.

Analysis of dynamic of two-phase flow in small channel based on phase space reconstruction combined with data reduction sub-frequency band wavelet

A new method of nonlinear analysis is established by combining phase space reconstruction and data reduction sub-frequency band wavelet. This method is applied to two types of chaotic dynamic systems(Lorenz and Rssler) to examine the anti-noise ability for complex systems. Results show that the nonlinear dynamic system analysis method resists noise and reveals the internal dynamics of a weak signal from noise pollution. On this basis, the vertical upward gas–liquid two-phase flow in a 2 mm × 0.81 mm small rectangular channel is investigated. The frequency and energy distributions of the main oscillation mode are revealed by analyzing the time–frequency spectra of the pressure signals of different flow patterns. The positive power spectral density of singular-value frequency entropy and the damping ratio are extracted to characterize the evolution of flow patterns and achieve accurate recognition of different vertical upward gas–liquid flow patterns(bubbly flow:100%, slug flow: 92%, churn flow: 96%, annular flow: 100%). The proposed analysis method will enrich the dynamics theory of multi-phase flow in small channel.

Fourier-shape-based reconstruction of rock joint profile with realistic unevenness and waviness features

Rock joint shape characteristics,waviness and unevenness play essential but distinct roles in shear mechanism of rock joints.This study presents a novel method to generate virtual rock joint profiles with realistic waviness and unevenness features.Firstly,joint profiles are obtained by 3D laser scanning device.Secondly,quantification of waviness and unevenness is conducted by traditional method,including digital filtering technique and roughness parameter RL.Thirdly,the discrete Fourier transform(DFT)method is employed to analyze the joint outlines.Two representative Fourier shape descriptors(D3,D8)for characterization of waviness and unevenness are suggested.Then,the inverse discrete Fourier transform(IDFT)is adopted to reconstruct the joint profiles with random values of phase angles but prescribed amplitudes controlled by D3 and D8.The traditional method is then applied to the reconstructed joint profiles to examine statistically the relationships between D3 and D8 and parameters RL of waviness and unevenness,respectively.The results show that larger D8 tends to result in larger waviness while higher D3 tends to increase unevenness.Reference charts for estimation of waviness and unevenness with different pairs of D3 and D8 are also provided to facilitate implementation of random joint reconstruction.

基于主成分变换的多光谱遥感数据的有监督可视化方法

【目的】遥感数据可视化是决定遥感数据解译质量高低的一个关键环节,目视解译是目前生产实践中遥感技术应用的一个重要方式。探讨一种基于学习样本生成可视化特征,使得可视化与目视解译应用能够有机结合,进而实现有监督可视化。【方法】采用主成分变换回归重构方法重构了针对森林资源的植被监测模型,得到3个新特征,依次赋予红绿蓝3种颜色以生成假彩色图像来实现信息可视化。【结果】基于学习样本的主成分变换回归重构方法与主成分变换法、原始近红外-短波红外-红波段组合相比,重构后的假彩色图像在一定程度上得到了改善,有利于目视解译。主成分变换回归重构后的分类精度比未重构的分类精度提高了6. 20%,比原始波段组合的分类精度提高了7. 82%。重构前后的一元和多元离差平方和(离差阵)构成变化分析说明,重构后类内差异缩小、类间差异增大。【结论】定量验证认为,主成分变换回归重构的可分性比未重构的主成分变换和原始波段组合的可分性都要好。

THE RECONSTRUCTION OF AN HERMITIAN TOEPLITZ MATRIX WITH PRESCRIBED EIGENPAIRS

This paper concerns the reconstruction of an hermitian Toeplitz matrix with prescribed eigenpairs. Based on the fact that every centrohermitian matrix can be reduced to a real matrix by a simple similarity transformation, the authors first consider the eigenstructure of hermitian Toeplitz matrices and then discuss a related reconstruction problem. The authors show that the dimension of the subspace of hermitian Toeplitz matrices with two given eigenvectors is at least two and independent of the size of the matrix, and the solution of the reconstruction problem of an hermitian Toeplitz matrix with two given eigenpairs is unique.