搜索资源列表
GL-25
- 基于新的交叉算子的全局与局部实数编码遗传算法GL-25-Global and local real-coded genetic algorithms based on parent-centric crossover operators
Immune-particle-swarm-algorithm
- 免疫粒子群算法，这种免疫粒子群优化算法结合了粒子群优化算法具有的全局寻优能力和免疫系统的免疫信息处理机制，并且实现简单，改善了粒子群优化算法摆脱局部极值点的能力。-Immune particle swarm algorithm, this immune particle swarm optimization PSO combines the global optimization ability of the immune system and immune mechanisms of info
LE
- from their own experiences. Usually there is no centralized control system dictating how individual particle will behave. It is the local interactions between particles that lead to the emergence of global behavior
ques6
- Write MATLAB code that will do the following. (a) Read a gray image and determine the histogram. (b) Equalize the histogram using normal and adaptive histogram equalization technique (Global). (c) Equalize the histogram using normal and adaptiv
sss
- - Color provide an important clue for extracting the new color LBP histogram features for face recognition using Local Binary Pattern technique. To reduce redundancy RGB color space converted to YCbCr color space. The Local Binary Pattern is a non pa
PSO
- 粒子群算法matlab代码，可运行，能找到函数的局部最值和全局最值。-Particle swarm algorithm matlab code, can run, the value of the value of local and global can find function.
hidden_feature_enhancement
- 这个脚本显示了如何使用本地局部和全局直方图共同加强图像,特别针对图像上有隐藏的部分。 利用了nlfilter()函数及循环遍历像素值修改。-This scr ipt shows to how to use local and global histograms to work together to locally enhance the image, especially suitable for the case that parts of the image may contain
Cloud-image-processing
- 处理云图数据，通过对云图加伪彩色便于观察分析，并且图像处理中设计了漫游、放大、缩小等功能，以便能对云图的全局或局部进行观察、分析。-Cloud data processing, through the cloud plus pseudo-color for easy observation and analysis, and image processing design roaming, zoom and other functions, in order to be able to clou
background-model8
- ：基于背景建模的运动目标分割是智能视频监控的重要任务，模型的质量直接影响到检测、跟踪、识别等运动分析的准确性．当前的建模方法多是单层的，忽略了像素特征在时域和空域上的联系，模型描述不够准确，对于背景扰动、全局光照变化及复杂的室内外场景等多种情况鲁棒性不强，导致了分割中出现空洞和噪声点．针对这些问题提出了一种双层建模的方法，在第一层提取时域上的像素亮度特征采用码本建模，第二层提取邻域纹理特征采用基于中心对称的局部二值模式建模．实验证明该方法在用于运动分割时，比常用方法具有更好的准确性和鲁棒性．-M
Simulated-Annealing-Tools-Software
- 模拟退火算法是通过赋予搜索过程一种时变且最终趋于零的概率突跳性，从而可有效避免陷入局部极小并最终趋于全局最优的串行结构的优化算法。-Simulated annealing algorithm is a time-varying by giving the search process and ultimately tends to zero the probability of jumps, thus can effectively avoid local minima and eventual
GA-BP
- GA—BP运用GA对BP神经网络进行训练，取得的最优解作为初始链接权值和阈值，以对BP神经网络局部搜索能力强、全局搜索能力差的缺点进行改进，来达到提高BP神经网络的性能的目的。-GA GA-BP using BP neural network is trained to obtain the optimal solution as the initial link weights and thresholds of BP neural network of local search abilit
DE-demo
- 微分进化算法是一种非常重要的参数寻有选择算法，可以有效的选择一些控制算法参数。-The differential evolution algorithm to search the global optimal solution of the stochastic optimization algorithm is an analog of the natural biological evolution. Because the differential evolution
Levenberg-Marquardt
- The LMA is a very popular curve-fitting algorithm used in many software applications for solving generic curve-fitting problems. However, as for many fitting algorithms, the LMA finds only a local minimum, which is not necessarily the global minimum.
multi-kernels-SVR
- 全局核（线性）与局部核（高斯）的加权组合，用于改进SVM的拟合和预测能力-The global kernel (linear) and local kernel (Gauss) weighted combination, to improve the SVM ability of fitting and prediction
KMeans
- K-均值聚类算法，属于无监督机器学习算法，发现给定数据集的k个簇的算法。 首先，随机确定k个初始点作为质心，然后将数据集中的每个点分配到一个簇中，为每个点找距其最近的质心， 将其分配给该质心对应的簇，更新每一个簇的质心，直到质心不在变化。 K-均值聚类算法一个优点是k是用户自定义的参数，用户并不知道是否好，与此同时，K-均值算法收敛但是聚类效果差， 由于算法收敛到了局部最小值，而非全局最小值。 K-均值聚类算法的一个变形是二分K-均值聚类算法，该算法首先将所有点作为一个簇，然
varible
- labview中全局变量、局部变量的一些应用实例，可以作为参考-Labview global variables, local variables in some application examples, can be used as a reference
Edge-Detection
- 与以往关注图像局部特征和局部连续性的方法不同，本文中的方法能够提取关于图像的全局印象。为此，我们将图像分割问题转化为图划分问题并提出了划分中的一种全局判别准则——Ncut (Normalized Cut)-Concerned with the past image local characteristics and continuity of local methods, the methods herein can extract images on the overall impressio
PSO
- Rosenbrock函数优化属于无约束函数优化问题，其全局极小值位于一条平滑而狭长的抛物线形状的山谷底部，且为优化算法提供的信息很少，因此找到其全局极小值就显得很困难。根据Rosenbrock函数的这种特性，专门提出了一种改进的PSO算法，该算法引入三角函数因子，利用三角函数具有的周期振荡性，使每个粒子获得较强的振荡性，扩大每个粒子的搜索空间，引导粒子向全局极小值附近靠近，避免算法过早地收敛，陷入局部最优，从而找到Rosenbrock函数的全局极小值。大量实验结果表明，该算法具有很好的优化性能，
bmvc06_lau_chung
- 医学图像配准，医学图像2D_3D配准，基于vc++开发。-Although the presence of local minima is one of the major problems in high-dimensional image registration, only a few experimental works have been carried out to address this problem. In this study, a 3D-2D vascular
NGA
- 小生境遗传算法，该算法易于找出优化问题的所有局部最优解和全局最优解-Niche Genetic Algorithm. The algorithm is easy to find the optimization problem in all local optimal solution and the global optimal solution