搜索资源列表
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global se
corner_detector
- 我用matlab写的一个corner detector, 效果比现在流行的harris，susan，CSS等效果要好。 Algorithm is derived from: X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support , Proceedings of the 17th International Co
Univariate_local_or_global_optimization
- Univariate local or global optimization matlab最优化工具包，可以进行最优化点的搜寻。
以K－均值聚类结果为初始解的模拟退火聚类
- 由于K－均值聚类算法局部最优的特点，而模拟退火算法理论上具有全局最优的特点。因此，用模拟退火算法对聚类进行了改进。20组聚类仿真表明，平均每次对K结果值改进8次左右，效果显著。下一步工作：实际上在高温区随机生成邻域是个组合爆炸问题（见本人上载软件‘k－均值聚类算法’所述），高温跳出局部解的概率几乎为0，因此正考虑采用凸包约束进行模拟聚类，相关工作正在进行。很快将奉献给各位朋友。-as K-means clustering algorithm for optimal local character
SURFACESMATCHINGALGORITHMBASEDONGENETICALGORITHMAN
- 针对基于最小二乘法的ICP 曲面匹配算法难以处理待比较曲面的局部大变形问题, 提出一种改进算 法。即采用遗传算法确定曲面初始相对位置以保证匹配优化结果为全局最优值, 利用ICP 算法匹配结果构造 偏差阈值, 以此阈值过滤点群后再以最小二乘法进行匹配处理, 消除局部大变形影响, 获得合理的变换矩阵。以此变换矩阵变换初始点群再进行误差计算, 从而获得理想的匹配结果-Least square method based on the ICP surface matching algorithm
LGIF
- 这是“Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation”（简称LGIF模型）的MATLAB源代码。LGIF模型是非常重要局部区域活动轮廓模型, 它结合了CV模型和LBF模型各自的优点。-This is the "Active contours driven by local and global inten
dp_align.tar
- 双序列比对:全局比对或局部比对算法，针对蛋白质序列或核酸序列-This program will do Needle global or Smith-Waterman local alignment for two protein sequences or DNA sequences
Steepest
- 计算梯度下降法计算极值，只能找到局部最小点。可以通过调整步长实现全局最小-Calculation of gradient descent method to calculate extreme value, can only find local minimum point. By adjusting the step size can achieve the global minimum
GA
- 本文针对传统遗传算法在求解问题的局限性如局 部收敛过快和全局“ 爬坡” 能力不强等问题, 提出一种改进的 控制策略, 最后通过实验验证算法的有效性。-In this paper, the traditional genetic algorithm in solving the problem of limitations such as fast local convergence and global " climbing" ability is not strong
jsjy20070288
- :针对遗传算法易陷入局部最优的不足,在标准遗传算法基础上加入了三个新的操作- 复原、重构和录优操作,使改 进后的遗传算法收敛于全局最优,并在此基础上以路边约束、动态避障和路径最短作为适应度函数,提出了动态避障的路径 规划方法。通过实验仿真验证了算法的有效性、准确性和实时性,并与基于以往的遗传算法的路径规划方法进行比较,结果 表明本文提出的方法在产生的路径长度和算法运行时间上都具有更优的性能。-: Genetic algorithm for the lack of easy to
SimulatedAnnealing
- Simulated Annealing (SA) is a smart (meta)-heuristic for Optimization. Given a cost function in a large search space, SA replaces the current solution by a random "nearby" solution. The nearby solution is chosen with a probability that depends on the
robotpathplanning
- Pioneer3机器人的路径规划程序。包括所有源代码。实现机器人在已知地图环境中的路径规划，包括全局的路径规划和局部的修正的路劲规划。是研究路径规划和动态避障绝好的例子。运行方式：先在服务端执行justPathPlanningGuiServer，然后执行MobileEyes查看规划结果。-Pioneer3 robot path planning process. Including all the source code. Known map of a robot path planning e
SOM_NOVELTY
- SOM-BASED METHODS FOR NOVELTY DETECTION Global Normality Profile Approach (GNP) Local Normality Profile Approach (LNP) First Global Then Local Normality Profiles Approach (FGTL)
SOM_PREDICTION
- SOM-BASED TIME SERIES PREDICTION Training Time Series Testing Time Series Local Linear Mapping (LLM) Vector-Quantized Temporal Associative Memory (VQTAM) Global RBF (GRBF, download here) and Local RBF (KRBF) Local AR predictors using data
SAPSO
- 权重改进粒子群算法中的自适应权重法，平衡了PSO算法的全局探索能力和局部改良能力-Weight improved particle swarm algorithm in the adaptive weighting method to balance the global exploration of the PSO algorithm is improved capacity and capacity of local
particle
- 本代码为经典PSO微粒群算法，通过修改w值，使得PSO的搜索在全局与局部之间得到最优-The code for the classic PSO particle swarm algorithm, by modifying the w value, makes the PSO search between the global and local optimal
threeer
- threshdemo.m Demonstration of global and local threshold operations of an image
Histeq
- 包含两个代码，分别是全局直方图均衡和局部直方图均衡，适用于不同情形-Global and local histogram equalization
newton2
- nonlinear optimization code can find local or global minima
IVC_code
- 论文Active contours with selective local or global segmentation: a new formulation and level set method. Image and Vision Computing, vol.28, issue 4, pp.668-676, April 2010.的源代码.简单,容易学习-code for Paper K.H.Zhang, Lei Zhang, H.H.Song and W.Zhou.,Active c