埃及加拿大--编队成形--针对成形的稳定性问题

Beschreibung zur wind turbine Tool Box

船舶参数横摇,参数横摇的3自由度模型，包括垂荡和纵摇作用(Parametric Rolling of ships, the 3 degree of freedom model of parametric rolling, including heave and pitch function )

逻辑无环流直流可逆调速系统的Matlab仿真(Logic Non-circulating DC Speed Control System Matlab simulation of reversible)

FOR HELP AND DOCUMENT FOR POWER cvd ffg

采用小波对信号分解和去噪。分解层数和使用的小波可以自己定义然后阈值去噪(Wavelet is used to decompose and denoise signals. The decomposition level and the use of wavelet can be defined by itself and then threshold denoising)

12.1 图像点的运算 12.1.1 线性点运算 12.1.2 非线性点运算 12.2 图像的算术运算 12.2.1 加法运算 12.2.2 减 法运算 12.2.3 乘法 运算 12.2.4 除法 运算 12.2.5 其它运算 12.3 图像的位逻辑运算 12.4 图像的几何运算 12.4.1 图像插值 12.4.2 图像缩放 12.4.3 图像旋转 12.4.4 图像剪切 12.5 空间变换 12.5.1 仿射变换（ affine transformation ） 12.5.2 透视变换 (Perspective Transformation) 12.5.3 空间变换的 MATLAB 函数 12.5.4 空间变换实例 12.6 图像融合 12.7 邻域与块操作 12.7.1 邻域操作 12.7.2 图像块操作 12.8 区域处理 12.8.1 区域选择 12.8.2 区域滤波 12.8.3 区域填充(12.1 image point arithmetic 12.1.1 computing linear point 12.1.2 nonlinear point operations 12.2 image adder computing 12.2.1 Arithmetic 12.2.2 subtraction multiplication 12.2.3 computing division 12.2.4 computing 12.2.5 other computing 12.3 Image 12.4 Image-bit logic operations geometric computing 12.4.1 Image Interpolation 12.4.2 image scaling 12.4.3 image rotation 12.4.4 Shear Image 12.5 Space Conversion 12.5.1 affine transformation (affine transformation) 12.5.2 Perspective Transform (Perspective Transformation) 12.5.3 space transform space transform MATLAB function 12.5.4 Examples 12.6 Image Fusion 12.7 Neighborhood and Block Operation 12.7.1 Operation 12.7.2 neighborhood image processing block operation 12.8 Regional 12.8 area selection 12.8.1. 2 regional filtering area filling 12.8.3)

改进的非负矩阵分解算法源程序 比较有用 直接可以使用(Negative matrix decomposition algorithm is more useful source program can be used directly)

F2T变换 (F2T transformation )

pca lda kpca klda lpp matlab 特征降为方法，对于新手比较有用。(pca lda kpca klda lpp matlab code for dimension reduction. these are very useful for new researchers.)

Ant Colony Optimization (ACO) is an optimization metaheuristic based on the foraging behavior of ants. This metaheuristic was originally proposed to find good solutions to discrete combinatorial problems. Many extensions of the ACO heuristic for continuous domain have been proposed, but even those that claim close similarity with classical (discrete domain) ACO, like ACOR, do not use the heuristic information called visibility, commonly used in the original ACO algorithm. In this paper, we show the importance of the visibility in ACO, by proposing ACOℝ -V , a variant of ACOR that performs better in a number of benchmark functions.