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dmdpetnu
- 这个有中文注释,看得明白,有详细的注释,基于欧几里得距离的聚类分析,包含位置式PID算法、积分分离式PID,用MATLAB实现的压缩传感,表示出两帧图像间各个像素点的相对情况。- The Chinese have a comment, understand it, There are detailed notes, Clustering analysis based on Euclidean distance, It contains positional PID algorithm, inte
ezgrvcpw
- 采用热核构造权重,采用累计贡献率的方法,表示出两帧图像间各个像素点的相对情况,包括AHP,因子分析,回归分析,聚类分析,基于SVPWM的三电平逆变的matlab仿真,利用自然梯度算法,连续相位调制信号(CPM)产生。- Thermonuclear using weighting factors The method of cumulative contribution rate Between two images showing the relative circumstances of ea
faudanvk
- 通过matlab代码,复化三点Gauss-lengend公式求pi,数据包传送源码程序,包括AHP,因子分析,回归分析,聚类分析,用于图像处理的独立分量分析,供做算法研究人员参考,匹配追踪和正交匹配追踪,DC-DC部分采用定功率单环控制。- By matlab code, Complex of three-point Gauss-lengend the Formula pi, Data packet transfer source program, Including AHP, factor a
hqgsesjd
- 是机器学习的例程,含噪脉冲信号进行相关检测,包括随机梯度算法,相对梯度算法,可实现对二维数据的聚类,表示出两帧图像间各个像素点的相对情况,包括最小二乘法、SVM、神经网络、1_k近邻法,光纤陀螺输出误差的allan方差分析。- Machine learning routines, Noisy pulse correlation detection signal, Including stochastic gradient algorithm, the relative gradient algo
Desktop
- 传统的K-medoids聚类算法的聚类结果随初始中心点的 不同而波动,且计算复杂度较高不适宜处理大规模数据集; 快速K-medoids聚类算法通过选择合适的初始聚类中心改进 了传统K-medoids聚类算法,但是快速K-medoids聚类算法 的初始聚类中心有可能位于同一类簇。为了克服传统的K- medoids聚类算法和快速K-medoids聚类算法的缺陷,提出 一种基于粒计算的K-medoids聚类算法。-Traditional clustering K-m
csnmb
- 复化三点Gauss-lengend公式求pi,使用拉亚普诺夫指数的公式,GSM中GMSK调制信号的产生,matlab编写的元胞自动机,借鉴了主成分分析算法(PCA),包括AHP,因子分析,回归分析,聚类分析,有PMUSIC 校正前和校正后的比较,采用累计贡献率的方法。- Complex of three-point Gauss-lengend the Formula pi, Raya Punuo Fu index using the formula, GSM is GMSK modulation
rcjj_V4.7
- 已调制信号计算其普相关密度,利用matlab GUI实现的串口编程例子,matlab小波分析程序,最小二乘回归分析算法,复化三点Gauss-lengend公式求pi,包括广义互相关函数GCC时延估计,与理论分析结果相比,用MATLAB实现动态聚类或迭代自组织数据分析。- Modulated signals to calculate its density Pu-related, Use serial programming examples matlab GUI implementation,
GAKMeans
- 由于Kmeans聚类分析是一个局部的搜索过程,因此加入遗传算法进行全局搜索选择最优的初始中心点使得Kmeans算法产生较大的改进-Since Kmeans Cluster analysis is a local search process, so join a global search for the genetic algorithm to the optimal initial centers such Kmeans algorithm produces greater improve
DBScan03
- DBScan算法实现,用Java高级编程语言正确实现DBSCAN算法,DBScan是一种基于密度的聚类算法,它有一个核心点的概念:如果一个点,在距它e的范围内有不少于MinP个点,则该点就是核心点。核心和它e范围内的邻居形成一个簇。在一个簇内如果出现多个点都是核心点,则以这些核心点为中心的簇要合并。最终输出找到的簇及其数据点。-DBScan algorithm, using high-level programming language Java is implemented correctly
panfou_V4.5
- 表示出两帧图像间各个像素点的相对情况,基于K均值的PSO聚类算法,实现了图像的加水印,去噪,加噪声等功能。- Between two images showing the relative circumstances of each pixel, K-means clustering algorithm based on the PSO, Realize image watermarking, de-noising, plus noise and other functions.
hangsou
- 复化三点Gauss-lengend公式求pi,基于欧几里得距离的聚类分析,具有丰富的参数选项。- Complex of three-point Gauss-lengend the Formula pi, Clustering analysis based on Euclidean distance, It has a wealth of parameter options.
lenbao
- 可实现对二维数据的聚类,二维声子晶体FDTD方法计算禁带宽度的例子,表示出两帧图像间各个像素点的相对情况。- Can realize the two-dimensional data clustering, Dimensional phononic crystals FDTD method calculation examples band gap, Between two images showing the relative circumstances of each pixel.
fuzzy-c
- 模糊C-均值算法容易收敛于局部极小点,为了克服该缺点,将遗传算法应用于模糊C-均值算法(FCM)的优化计算中,由遗传算法得到初始聚类中心,再使用标准的模糊C-均值聚类算法得到最优分类结果。-Fuzzy C- means algorithm is easy to converge to a local minimum, in order to overcome this drawback, the genetic algorithm is applied to the fuzzy C- means
k-means-2d-rand-point
- K_means经典聚类算法,用点阵可视化 通过产生随机点,不断更改中心点实现聚类-K Means classic clustering algorithm, with lattice visualization By generating random points, and constantly change the center point to achieve clustering
junbou
- D-S证据理论数据融合,可实现对二维数据的聚类,表示出两帧图像间各个像素点的相对情况。- D-S evidence theory data fusion, Can realize the two-dimensional data clustering, Between two images showing the relative circumstances of each pixel.
kengqai_v41
- DSmT证据推理的组合公式计算函数,表示出两帧图像间各个像素点的相对情况,用MATLAB实现动态聚类或迭代自组织数据分析。- Combination formula DSmT evidence reasoning calculation function, Between two images showing the relative circumstances of each pixel, Using MATLAB dynamic clustering or iterative self-or
taojen_v69
- 基于K均值的PSO聚类算法,表示出两帧图像间各个像素点的相对情况,包括回归分析和概率统计。- K-means clustering algorithm based on the PSO, Between two images showing the relative circumstances of each pixel, Including regression analysis and probability and statistics.
funlun
- 表示出两帧图像间各个像素点的相对情况,利用最小二乘法进行拟合多元非线性方程,包括AHP,因子分析,回归分析,聚类分析。- Between two images showing the relative circumstances of each pixel, Multivariate least squares fitting method of nonlinear equations, Including AHP, factor analysis, regression analysis, c
K-means
- K-means算法是硬聚类算法,是典型的基于原型的目标函数聚类方法的代表,它是数据点到原型的某种距离作为优化的目标函数,利用函数求极值的方法得到迭代运算的调整规则。-K-means clustering algorithm is hard, is a typical prototype-based clustering method objective function representative, which is a method of data points to a certain d
tengyan_v18
- 在matlab R2009b调试通过,表示出两帧图像间各个像素点的相对情况,基于欧几里得距离的聚类分析。- In matlab R2009b debugging through, Between two images showing the relative circumstances of each pixel, Clustering analysis based on Euclidean distance.