一种合成聚焦的便携式B型超声成像方法

传统合成聚焦超声成像方法在图像重建过程中处理数据量较大,致使其在便携式B型超声设备中应用受限。针对该问题,提出一种基于压缩感知理论和合成聚焦波束形成算法的便携式B型超声成像方法(SFCS)。该方法通过对接收到的射频回波信号进行随机采样得到欠采样的测量信号,将测量信号经过合成聚焦波束形成处理获得欠采样的射频信号线,基于压缩感知的信号重构算法,由欠采样的射频信号线高质量地恢复信号后供后续成像处理使用。仿真实验结果表明,SFCS可有效地解决合成聚焦超声成像过程中数据量大的问题,从而在保证较高成像质量的前提下满足便携式B型超声设备小型化、低成本的技术要求,具有工程应用价值。     

基于压缩感知的图像重构算法

在图像压缩感知中,梯度投影恢复算法存在收敛速度慢、迭代次数多、对数据稀疏度过分敏感的问题。为此,提出一种基于压缩感知的图像重构算法。将拟牛顿法引入稀疏梯度投影算法中,利用拟牛顿法的估计校正机制以及其全局超线性收敛性,通过对目标函数的校正,获得更精确的搜索方向,从而减少迭代次数,构成有效收敛的图像恢复算法。实验结果表明,与传统梯度投影恢复算法相比,该算法在保证较好图像恢复效果的同时具有较好的抗噪性能,并且在减少迭代次数的基础上能有效降低重构误差,得到稳定收敛的重构结果。     

区间数信息下的多属性群决策研究

随着决策系统的不断扩大以及复杂化,评价指标以实数值描述稍显欠妥。研究属性权重为实数值、区间数信息下的多属性群决策问题,建立集结区间数信息的非线性规划模型,采用模拟植物生长算法集结各方案中多位专家给出的区间数偏好,并利用得到的偏好区间数构成群决策偏好矩阵。结合已知权重,引入投影理论得到各方案的综合评价值,从而选出最优决策方案。算例结果表明,模拟植物生长算法不仅计算简便、灵活,并且尊重每个专家的意见,较好地保留了信息的完整性,显示出人工智能算法在信息集结方面的有效性。     

Adaptive Face Recognition via Structed Representation

In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspaee approach to classify the test sample. In order to adapt all the eases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low ~ample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.     

PROJECTION MODULUS: A NEW DIRECTION FOR SELECTING SUBSET AUTOREGRESSIVE MODELS

Selecting a parsimonious subset autoregressive time series model is a valuable objective particularly where there is or may be evidence that a time series may have some form of periodic or quasi-periodic behaviour. An efficient model selection procedure is essential because of the large number of possible alternative models involved. The explanation of an increase in residual variance due to excluding a lag is examined in Hilbert space. As a result, a new statistic, the projection modulus , and its derivatives are developed to assess the significance of any lag in a model. The impact of deleting a lag, as measured by these statistics, helps to produce a selection procedure where true lags have less chance of being removed. We then assess an efficient subset autoregressive model selection procedure employing these statistics. The success of the proposed procedure is illustrated by its efficiency in identifying the true model for simulated and real data.     

Visual experience for autostereoscopic 3D projection display

In order to investigate visual experience for watching the autostereoscopic three‐dimensional (3D) projection display, we conduct a subjective evaluation experiment by a questionnaire when viewing video clips. Factor analysis is adopted to classify the evaluation items for the perpetual constructs of visual experience. Then a mixed design with repeated measurement analysis of variance with dimension and display duration as factors is carried out on the evaluation data to check the factorial effects and interactions for statistical significance. The results of factor analysis extract five factors including visual comfort, image quality, distortion, naturalness, and presence, which can be used as comprehensive indicators to evaluate the autostereoscopic 3D projection display. The results of analysis of variance indicate that image quality, which is used to assess two‐dimensional contents, is no longer applicable. It is necessary to give consideration to depth when evaluating 3D visual experience. Although 3D scenes enhance the overall subjective performance such as naturalness and presence, the health issues and stereoscopic distortion related to the introduction of depth cannot be ignored.     

考虑空气阻力的抛体最大射程和最佳抛射角研究

为了研究抛体在什么抛射角抛出时具有最大射程,利用拉格朗日乘子法,推导出存在空气阻力并且起点和终点不在同一高度时,在某一斜面上抛出的抛体的最大射程和最佳抛射角.通过计算机编程,以计算投掷手榴弹时的最大射程和最佳抛射角为例进行验证,并对物理教学中抛体运动的动力学过程进行了进一步的分析和讨论,有利于提高教学效果.     

基于球门检测的足球视频精彩事件提取

为了提高足球视频精彩事件检测效率,提出了一种基于双投影法的球门镜头检测算法,并在此基础上提出了基于球门检测的精彩事件提取算法.实验结果表明,该算法比常规算法取得了更好的检测效果,生成的精彩视频摘要大约为原视频的5%.     

结构损伤识别的残余向量法及数值仿真

为了找到对小损伤较敏感的参数,在结构自由振动微分方程基础上,利用广义逆和矩阵投影定理,导出了识别效果很好的残余向量投影范数.确定了损伤单元,计算了该损伤单元的损伤因子.算例分析发现,该参数对结构损伤非常敏感,能识别出结构中的微小损伤,而且不受损伤位置的约束,仅需要结构的前几阶模态就能达到很好的效果.     

一类广义集值强非线性混合拟变分不等式(英文)

引进一类广义集值强非线性混合拟变分不等式,并且用投影技巧证明了它解的存在性.推广了广义集值强非线性混合变分不等式的许多结论.