2f光电混合匹配滤波相关识别研究

提出一种光电混合匹配滤波相关识别方法,只用一个空间光调制器实现了匹配滤波相关识别。利用计算机完成匹配滤波器的设计以及匹配滤波器与输入目标频谱的卷积运算,根据最小欧氏投影编码原理将卷积结果转化为空间光调制器可以显示的灰度信号,再通过2f光学傅里叶变换系统,得到相关识别结果。实验结果表明,该方法可以得到明显的相关点,同时可以避免传统VLC中匹配滤波器的精确复位问题,而且该系统还可以应用于联合变换相关识别。     

Simple and flexible generation of vestigial side band modified duobinary return-to-zero signals at 10, 20 and 40 Gb/s

We propose and demonstrate a simple and flexible approach to generate vestigial side band modified duobinary return-to-zero (VSB MD-RZ) signals at 10-40 Gb/s, using a dual-drive Mach-Zehnder modulator and a detuned optical band-pass filter. The performance of the proposed VSB MD-RZ signal is investigated by comparing with double side band MD-RZ (DSB MD-RZ) and conventional VSB MD-RZ. Bit error ratio (BER) measurement at 10 Gb/s shows an error free operation for the generated signal. Good performance is further observed after 100 km of single-mode-fiber transmission at 40 Gb/s.     

Blood flow evaluation in high-frequency, 40 MHz imaging: A comparative study of four vector velocity estimation methods

Ultrasonic imaging is often used to estimate blood flow velocity. Currently, estimates are carried out using Doppler-based techniques. However, there are a number of shortcomings such as the limited spatial resolution and the inability to estimate longitudinal flows. Thus, alternative methods have been proposed to overcome them. Difficulties are notably encountered with high-frequency imaging systems that use swept-scan techniques. In this article, we propose to compare four vector velocity estimation methods that are complementary to Doppler, focusing on 40 MHz, high-frequency imaging. The goal of this study is to evaluate which method could circumvent the limitations of Doppler methods for evaluation of microcirculation, in the vessels having diameter on the order of 1 mm. We used two region-based approaches, one decorrelation-based approach and one spatiotemporal approach. Each method has been applied to seven flow sequences with various orientations and mean velocities. Four sequences were simulated with a system approach based on a 3D set of moving scatterers. Three experimental sequences were carried out by injecting blood-mimicking fluid within a gelatin phantom and then acquiring images with Visualsonics, Vevo 660 system. From velocity estimates, several performance criteria such as the normalized mean error or the normalized mean standard deviation were defined to compare the performance of the four estimators. The results show that region-based methods are the most accurate exhibiting mean errors less than 10% and mean standard deviation less than 13%. However, region-based approaches are those that require the highest calculative cost compared to the decorrelation-based method, which is the fastest. Finally, the spatiotemporal approach appeared to be a trade-off in terms of computational complexity and accuracy of estimates. It provides estimates with errors less than 10% for mean velocity and the CPU time is approximately 17 s for a ROI of size 40 * 80 pixels.     

Exact asymptotics in eigenproblems for fractional Brownian covariance operators

Many results in the theory of Gaussian processes rely on the eigenstructure of the covariance operator. However, eigenproblems are notoriously hard to solve explicitly and closed form solutions are known only in a limited number of cases. In this paper we set up a framework for the spectral analysis of the fractional type covariance operators, corresponding to an important family of processes, which includes the fractional Brownian motion and its noise. We obtain accurate asymptotic approximations for the eigenvalues and the eigenfunctions. Our results provide a key to several problems, whose solution is long known in the standard Brownian case, but was missing in the more general fractional setting. This includes computation of the exact limits of $L^2$-small ball probabilities and asymptotic analysis of singularly perturbed integral equations, arising in mathematical physics and applied probability.     

Optimal stopping of a Brownian bridge with an unknown pinning point

The problem of stopping a Brownian bridge with an unknown pinning point to maximise the expected value at the stopping time is studied. A few general properties, such as continuity and various bounds of the value function, are established. However, structural properties of the optimal stopping region are shown to crucially depend on the prior, and we provide a general condition for a one-sided stopping region. Moreover, a detailed analysis is conducted in the cases of the two-point and the mixed Gaussian priors, revealing a rich structure present in the problem.     

Semiparametric spatio‐temporal analysis of regional GDP growth with respect to renewable energy consumption levels

This article evaluates the impact of renewable energy consumption levels on GDP growth. Renewable energy sources may be significantly more costly as compared to classical (fossil) sources. Hence, high relative proportion of renewable energy has the potential of obstructing economic growth. On the other hand, in developed countries, renewable energy adoption processes are often subject to prominent state‐level incentives, administrative ingerence, and fiscal subsidies. For stratified and unbiased evaluation of the overall effect of renewables on GDP, this article applies a spatio‐temporal analysis of GDP growth at the regional NUTS2 level in a conveniently selected group of 11 spatially adjacent yet heterogeneous EU member states. As macroeconomic covariates are controlled for, along with spatial and temporal interdependencies, there is no sign of negative impact of renewable energy consumption on GDP growth. While the estimated overall effect is positive and statistically significant, its economic significance is small. Yet, given the data and economies considered, we may conclude that renewable energy consumption does not exert negative influence on economic growth rates.     

Sequential Bayesian learning for stochastic volatility with variance‐gamma jumps in returns

In this work, we investigate sequential Bayesian estimation for inference of stochastic volatility with variance‐gamma (SVVG) jumps in returns. We develop an estimation algorithm that combines the sequential learning auxiliary particle filter with the particle learning filter. Simulation evidence and empirical estimation results indicate that this approach is able to filter latent variances, identify latent jumps in returns, and provide sequential learning about the static parameters of SVVG. We demonstrate comparative performance of the sequential algorithm and off‐line Markov Chain Monte Carlo in synthetic and real data applications.     

黄河河道冰水情定点连续自动检测及数据分析

根据黄河中上游流域冰水情监测以及预防凌汛灾害的需求,设计了一种适合黄河河道的冰水情自动测报系统.该系统由基于空气、冰与水电阻特性差异的冰层厚度传感器、DS18B20的温度梯度传感器以及智能处理仪构成.采用该系统在内蒙托克托县黄河河道进行了黄河封冻期河道冰层厚度连续监测试验,获取了大量的现场实测数据,对采样数据进行分析,提出了判别冰层厚度的平均滤波算法,实现了对冰层生消变化全过程的自动监测.     

枪支弹头痕迹自动对比方法研究

建立了枪支弹头痕迹的自动识别模型.解决了细微信息提取,误差校正,特征位置选取等问题.以11只枪,22颗子弹的三维数据作为测试数据,模型的最高识别率达到77%.     

一类非平稳随机传递系统的最佳非线性滤波及优化算法

运用最佳非线性滤波方法及优化算法,讨论了一类不完全数据与具有连续时间的非平稳随机过程的最佳控制问题,得到了这两种状态下的两个最佳控制数学模型,给出了这类非平稳随机传递系统的最佳编码与最佳译码的建立方法,为解决这类非平稳随机过程的最佳控制提供了一种有效可靠的解决方法.