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fmincon
- 局部优化，能够求出最小值，如果给出了一个范围-Local optimization, can be obtained a minimum, if a range is given
空间插值方法汇总
- Inverse Distance to a Power（反距离加权插值法） Kriging（克里金插值法） Minimum Curvature（最小曲率） Modified Shepard s Method（改进谢别德法） Natural Neighbor（自然邻点插值法） Nearest Neighbor（最近邻点插值法） Polynomial Regression（多元回归法） Radial Basis Function（径向基
CameracaUbraifonformonocularvision
- 摄像机标定是计算机视觉领域的一个研究热点，为了解决单目摄像机标定中的精度不高、模型复杂、鲁棒性差等问题，依 据神经网络、遗传算法及摄像机标定的特点，提出了基于遗传算法和BP神经网络相结合的单目摄像机标定方法。该方法充分利用 遗传算法的全局优化和神经网络的局部收敛的特点，一方面避免了建立复杂的摄像机成像模型，另一方面增强了摄像机标定的精 度和鲁棒性。-The camera calibration isoneofmostimportantresearch ifeldsin compute
SAR-image-segmentation-method
- 为了减少alpha-expansion算法的计算量，本文在标号为alpha的像素向其它像素膨胀的过程中，先隔离非alpha类间的联系，而只考虑alpha类与非alpha类之间的关系，从而避免alpha-expansion算法需要构造辅助结点的问题，减少了s/t图中边的数目，提高了算法的计算效率。因放松了非alpha类间的关系对alpha膨胀的约束，使得算法可以更容易得跳出能量函数的局部极小点而获得更优的分割结果。-In order to reduce alpha- expansion algor
Active-Contour-Models-
- 传统Snake 模型存在的缺点是, 其初始轮廓必须靠近图像中感兴趣目标的真实边缘,否则会得到错误结 果,且由于Snake 模型的非凸性,结果不能进入感兴趣目标的深凹部分,很容易陷入局部极小点. 由此该文提出一 种基于力场分析的主动轮廓模型,详细分析了基于欧氏距离变换的距离势能力场分布,归纳出感兴趣目标上真轮 廓点与假轮廓点的判别标准. 建立了由曲线能量到最终结果的有效方法,避免了Snake 陷入局部极小点. 实验结果 表明,该模型具有较大的捕获区域,能够进入感兴趣目标的深凹部分
A-hybrid
- 针对传统的ＢＰ或ＧＡ对模糊神经网络的识别应用存在收敛容易陷入局部极小 识别率低下等问题 提出一 种基于ＢＦＧＳ的混合遗传算法 其基本思想为 首先构造一种前馈型模糊神经网络结构 然后用遗传算法进化若干代 后 当目标函数的梯度或者范数小于预先设定值 则改用ＢＦＧＳ算法进行优化识别 仿真实验表明 对比ＧＡ该算法 收敛速度较快 识别精度提高了约７％ 能够较好地应用于一类模糊神经网络的识别-In traditional BP or GA to identify the application
xcvb
- Watershed segmentation method is a topology-based theory of mathematical morphology segmentation method, the basic idea is the image as a geodesic topology on the landscape, the image pixel gray value of each point indicates that the point of the alt
Rainvc
- fsdfđ gdWatershed segmentation method is a topology-based theory of mathematical morphology segmentation method, the basic idea is the image as a geodesic topology on the landscape, the image pixel gray value of each point indicates that the poin
FIbonachii-method-cSharp
- Method for finding local maxima or minimum using fibonachii.
SA-TSP
- Simulated Annealing (SA) is the oldest probabilistic meta-heuristic algorithm and one of the first algorithms having ability to avoid being trapped in local minima. It is inspired by the process of annealing in metallurgy. In this process a m
Boltzmann-machine-algorithm
- 波尔兹曼机算法，一种流行的人工神经网络算法，可解决局部最小等问题-Boltzmann machine algorithm, a popular artificial neural network algorithm, solve the local minimum problem
Study-of-Improved-BP-Neural-Network-on-Rotor-Spee
- In this paper three different methods such as GDM AGDM and modified PSO are adopted to optimize the neural networks, and simulate the DTC system with MATLAB/SIMULINK. The result shows: modified PSO algorithm can solve the problem of neural n
Design-of-a-fast-convergent-backpropagation
- The main contribution of this paper is using optimal control theory for improving the convergence rate of backpropagation algorithm. In the proposed approach, the learning algorithm of backpropagation is modeled as a minimum time control prob