迭代次数

This paper discusses the nonlinear inversion algorithms instructively andmainlystudytwokinds ofnonlinearinversionalgorithms: SimulatedAnnealingConjugate Grads and Artificial Neural Network Genetic Algorithms, these two methods can decrease the iteration times and avoiddroppinginto the local extremum, we do the model calculation and confirm thevalidityofthealgorithm.

对非线性反演算法进行了有益的探讨，主要研究了两种非线性混合优化反演算法：模拟退火共轭梯度混合反演和神经网络遗传反演算法，两种混合算法都达到了减少迭代次数、避免陷入局部极值的目的，并进行了模型试算，验证了算法的有效性。

With the increasing of iterations, the channel performance is better.

随着迭代次数的增加，信道性能越好。

How the number of the particles and the iterations influence the speed of the synthesis is analyzed in detail.

并对算法执行中的粒子数、迭代次数对合成速度和合成效果的影响进行了详细的分析。

Now we are able to use the turbosmooth with 2 iterations.

现在我们可以使用turbosmooth修改器了，迭代次数设置为2。

The results show that the target contour can be accurately extracted. While the iterative and computation time is reduced.

分割结果表明，该方法能够准确地提取出目标轮廓，同时减少了迭代次数和运算时间。

The results show that the target contour can be accurtely extracted. While the iterative and computation time is reduced.

分割结果表明，该方法能够准确地提取出目标轮廓，同时减少了迭代次数和运算时间。

An automatic FEM refining method is presented in this way,a method of creating transition elements is introduced,and then the refine mesh is analyzed according to the times of iterative educed from computation.

以此提出一种自动的有限元精细划分的算法。介绍构造过渡单元的方法，并根据计算出的迭代次数，得到细网格后进行分析。

Power Extrapolation uses eigenvalues directly in the process of iterating hyperlink-based Markov matrix.

Power Extrapolation算法通过特征值直接求解马尔可夫超链接矩阵的主特征向量，但该算法的迭代次数与参数d的选择密切相关。

In this paper, the theory, algorithm, and experiment of automatic object detection and tracking are studied in depth. It is firstly pointed out that the essential of Mean Shift method is a special Newton-Gaussian method. A new method named Fast Mean Shift is established to stretch the conservative step of Mean Shift method. The convergence and validity of this new method are proved in theory. And it is also proved that the convergence speed of Fast Mean Shift is faster than that of Mean Shift. The contrast experiments of searching the maximum possibility density of random of data sets in plane and 3D space are done. The results show that this new method can reduce the iterations greatly. A new object tracking method based on Fast Mean Shift is built to improve the object tracking performance, which is shown in the face tracking experiment with the tennis sequence provided by the Ohio State University, and the car tracking experiment with the car sequence provided by Kalsruhe University. The face trcking experiment with highly noised images show that the object tracking method based on Fast Mean Shift has strong anti-jamming ability. A new fast color object detection technology based on characteristic color is established, which use characteristic color distribution to compute the characteristic color vector of any area in an image quickly. With the high performance search method, the fast object detection is achieved. At last, using object tracker based on Fast Mean Shift and color object detector based on characteristic color with the Kalman filter, PID controller, searial communication and other technologies, automatic object detection and tracking system with control system is built. The availability and anti-jamming ability of this system are verified by some object detection and tracking tests in different scenes.

本文对目标自动识别与跟踪进行了理论、计算、试验三方面的深入研究，主要包括：首次指出了目标跟踪技术中常用的均值迁移方法的本质为一种特殊的高斯-牛顿方法，改进了均值迁移方法步长取值保守的弱点，建立了快速均值迁移方法，证明了该方法的收敛性、有效性以及收敛速度优于均值迁移方法；进行了平面和3维随机分布数据集的最大概率密度搜索对比试验，试验结果表明，快速均值迁移方法大大减少了迭代次数；建立了基于快速均值迁移的目标跟踪方法，利用俄亥俄州立大学提供的乒乓球序列图像和卡斯鲁厄大学的汽车序列图像，对人脸和汽车目标跟踪性能分别进行了对比试验，并进行了高噪声人脸图像目标跟踪试验，结果表明，基于快速均值迁移的目标跟踪方法有效提高了目标跟踪性能，具有很强的抗干扰能力；建立了一种新型彩色目标自动识别方法，采用特征色彩分布函数实现了对任意图像区域特征色彩矢量的快速计算，建立了高效的搜索方法，实现了彩色目标的快速识别；将基于快速均值迁移方法的目标跟踪方法、基于特征色彩的目标识别方法与卡尔曼滤波、PID控制、串行通讯等技术结合，建立了带有控制系统的快速目标自动识别与跟踪系统，并在不同场景下进行了目标自动识别与跟踪试验，验证了快速目标自动识别与跟踪系统的有效性和抗干扰能力。

Parameters simplification of dynamic relaxation method is an improvement of the traditional method, and the increment of iteration is so small that this promoted method is worthy of further studying.

参数简化的动力松弛法是对传统动力松弛法的改进，而计算迭代次数比原来提高不多，因此，本方法值得尝试与进一步研究改进。

This one mode pays close attention to network credence foundation of the businessman very much.

这一模式非常关注商人的网络信用基础。

Cell morphology of bacterial ghost of Pasteurella multocida was observed by scanning electron microscopy and inactivation ratio was estimated by CFU analysi.

扫描电镜观察多杀性巴氏杆菌细菌幽灵和菌落形成单位评价遗传灭活率。