基于Voronoi图和动态自适应蚁群算法的UAV航迹规划

以UAV航迹规划为应用背景,提出了一种基于Voronoi图和动态自适应蚁群算法的航迹规划方法;为了提高航迹规划问题最优解的质量及全局求解能力,克服传统蚁群算法收敛速度慢、容易陷入局部最优等缺点,提出了一种动态自适应蚁群算法;采用动态自适应航迹点选择策略并将信息素更新规则和挥发系数进行动态自适应调整变化来对蚁群算法进行了改进,提高了算法的求解效率;根据战场已知威胁源生成Voronoi加权图,并与所提的动态自适应蚁群算法相结合求解规划空间中的最优航迹;考虑到UAV的物理约束限制,对生成的可行航迹进行平滑优化;仿真结果表明,该方法能够为UAV规划出一条满足要求的可飞航迹,验证了所提方法在解决航迹规划问题时是可行、有效的;     

Computing the Loewner Driving Process of Random Curves in the Half Plane

We simulate several models of random curves in the half plane and numerically compute the stochastic driving processes that produce the curves through the Loewner equation. Our models include models whose scaling limit is the Schramm-Loewner evolution (SLE) and models for which it is not. We study several tests of whether the driving process is Brownian motion, as it is for SLE. We find that testing only the normality of the process at a fixed time is not effective at determining if the random curves are an SLE. Tests that involve the independence of the increments of Brownian motion are much more effective. We also study the zipper algorithm for numerically computing the driving function of a simple curve. We give an implementation of this algorithm which runs in a time O(N ^1.35) rather than the usual O(N ²), where N is the number of points on the curve.     

高光谱成像技术的柑橘植株叶片含氮量预测模型

氮素是果树生长发育的一种大量必需元素,及时准确地监控果树的氮营养状况,对果树的合理施肥、增产、优化果实品质以及减缓过量施氮引起的水资源污染具有重要意义。利用高光谱成像技术结合多变量统计学方法,建立了柑橘植株叶片的含氮量预测模型。研究步骤为：高光谱扫描、提取平均光谱曲线、预处理原始光谱数据、采用连续投影法提取特征波段和建立含氮量预测模型。从SG平滑、SNV、MSC、1-Der等11种预处理方法中筛选出的较优预处理方法是SG平滑、Detrending和SG平滑-Detrending。对应这三种最优预处理方法,先采用连续投影法挑选出各自的特征波长,然后将各特征波段下的光谱反射率作为偏最小二乘、多元线性回归和反向传播人工神经网络模型的输入,各自建立三个预测模型。从以上获得的9个预测模型中,得出两个最优模型SG平滑-Detrending-SPA-BPNN(R_p：0.851 3,RMSEP：0.188 1)和Detrending-SPA-BPNN(R_p：0.8609,RMSEP：0.159 5)。结果表明,利用高光谱数据测定柑橘叶片含氮量具有可行性。这为实时、准确地监控柑橘植株生长过程中叶片含氮量的变化以及合理科学的氮肥施加提供了一定的理论基础。     

基于数学形态学的弱点状运动目标的检测

提出了一种新的基于数学形态学的红外图像序列中弱点状运动目标的非参数检测算法。采用数学形态学抑制背景杂波干扰和增强目标,用沿时间轴投影和二维空域搜索代替复杂的时空三维搜索形成组合帧,然后在每条可能的轨迹上将进行目标能量累加,实现了一种快速检测前跟踪(TBD)检测算法。仿真实验表明:在恒虚警概率条件下,该检测算法能高效地检测信噪比约为2的弱点状运动目标,检测性能对噪声分布不敏感,能精确地得到目标的即时位置和速度信息,适合于实时图像处理和目标探测,具有很高的实用价值。     

基于模糊技术的非线性系统目标跟踪融合算法

提出了一种基于模糊技术的非线性系统中多传感器目标跟踪融合算法.在基于卡尔曼滤波器的分布式融合算法中,利用模糊技术中的决策距离思想,对实时跟踪目标的多传感器进行动态分组,以获得在非线性系统中目标跟踪的最佳融合数据精度.仿真结果证明,该算法是一种有效的分布式融合算法.     

PCS颗粒测量技术中的累积分析方法研究

采用Levenberg-Marquardt法对累积分析方法中初始值的选择问题进行了分析和研究,并采用此方法对50 nm,100 nm,200 nm,300 nm,500 nm的标准聚苯乙烯乳胶颗粒的实测数据进行了拟合,通过与传统的累积分析法拟合结果对比,采用Levenberg-Marquardt法改进的累积法不但可以给出稳定的颗粒粒径,而且减小了拟合结果的误差.     

A novel pose and illumination robust face recognition with a single training image per person algorithm

In the real-world application of face recognition system, owing to the difficulties of collecting samples or storage space of systems, only one sample image per person is stored in the system, which is so-called one sample per person problem. Moreover, pose and illumination have impact on recognition performance. We propose a novel pose and illumination robust algorithm for face recognition with a single training image per person to solve the above limitations. Experimental results show that the proposed algorithm is an efficient and practical approach for face recognition.     

Detection of delamination defects in CFRP materials using ultrasonic signal processing

In this paper, signal processing techniques are tested for their ability to resolve echoes associated with delaminations in carbon fiber-reinforced polymer multi-layered composite materials (CFRP) detected by ultrasonic methods. These methods include split spectrum processing (SSP) and the expectation-maximization (EM) algorithm. A simulation study on defect detection was performed, and results were validated experimentally on CFRP with and without delamination defects taken from aircraft. Comparison of the methods for their ability to resolve echoes are made.     

光声成像技术的最新进展

光声成像技术是生物医学领域中新兴的无损检测技术,具有对比度高、分辨率好、穿透能力强等优点.本文介绍了光声成像技术近年来的进展状况,主要涉及成像探测方式的改进、成像速度的加快、成像分辨率的提高以及图像重构算法的发展等.以该项技术在现代临床诊断中的应用为例,描述了其在生物医学领域中应用范围的拓宽.最后,总结了该项技术现存的...