Reconstruction_of_oversampled_cosine-modulated_fil

用matlab编写，实现了GPS信号的仿真(Prepared using matlab to achieve a GPS signal simulation)

a document ppt on how to perform fingure print recognition .....

这是一个matlab读取视频的例子，这种东西我新接触，不知道大家要不要。我觉得不错。(read Matlab video examples, this thing I new contacts do not know if you want to. I think it's good.)

Example: A = double(imread( fingerprint.png ))/255 B = coherencefilter(A,4, sigma ,1.5, rho ,5) image(min(max(B,0),1)) axis image [1] Weickert, J. 1996. Anisotropic Diffusion in Image Processing. Ph.D. Thesis, Dept. of Mathematics, University of Kaiserslautern, Germany, pp. 42-43, 80-82, 107. Pascal Getreuer 2008-2009

TE多模态数据，可用于多模态过程监控，检验算法(TE multimodal data can be used for multimodal process monitoring and verification algorithm)

说明：  matlab图像相关性计算，根据相关性系数计算公式编写(matlab image correlation calculated correlation coefficients according to formula preparation)

Matlab入门介绍电子教程：MAT L A B能做什么(textbook of matlab)

modified NSGA-II for job sequencing problem

matlab小程序，实现曲线的自动拟合，采用傅里叶拟合方程(matlab small program to achieve the automatic curve fitting, Fourier fitting equation)

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，为某些领域某些特定的类似于Rosenbrock函数的优化问题提供了一种新的思路。(Rosenbrock function optimization functions are unconstrained optimization problems, its global minimum value at a smooth parabolic shape and narrow mountain valley Department, and for the optimization algorithm provides little information, and therefore find its global minimum value becomes very difficult. According to this feature Rosenbrock function, specifically mentioning Out an improved PSO algorithm (PSO-R), the algorithm introduced trigonometric factor, using trigonometric has periodic oscillations, so that each particle to obtain more Strong oscillations of expanding the search space of each particle, the particle is close to nearby guide global minimum, avoiding premature convergence algorithm, into a local optimum, thus Finding the global minimum Rosenbrock function. Experimental results show that the algorithm has a good optimizing performance, similar to some certain areas Rosenbrock function in the optimization problem provides a new way of thinking.)