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说明：  matlab方面的资料！是学习Matlab的好资料！！！！！(this is matlab ,matlab learnings,can learning more from it!)

利用神经网络进行台风分类的matlab程序，主要将台风分成三个阶段。(Using neural network the typhoon classification Matlab program, the main typhoon is divided into three stages.)

ifft和fft实现线性卷积,并与matlab中默认内置的conv()函数的结果对照，验证其正确性。(using ifft and fft to accomplish linear conviction. Comparing this method with matlab default function conv().)

DEOS Matlab InSAR tolbox version 1.1， 包含针对Doris产品的仿真、可视化脚本，以及去线性趋势、多视处理等。(It contains scripts for simulation, visualization of the products of Doris, and for additional processing (trend removal, multilooking, etc.).)

产生高斯分布随机变量方法的Matlab脚本，运用该小程序可以方便产生高斯分布随机变量(Random variables have a Gaussian distribution methods Matlab script, use the small program can easily generate Gaussian distributed random variables)

说明：  1、以不同的视角观察球面 和圆柱面 所围区域。2、画出s(t)=cos(2/3πf0t)的曲线及其付氏变换的曲线.设:f0=1KHz,时域分辨率 dt=0.01ms, 采样点数 N=2k, k>10.（均为M文件）(One to observe the different angles of spherical and cylindrical surface region by Wai. 2, draw s (t) = cos (2/3πf0t) curve and its Fourier transform curve. Established: f0 = 1KHz, time-domain resolution of dt = 0.01ms, sampling points N = 2k, k)

本文基于毕肖普法和蒙特卡洛法,利用MATLAB编程软件计算了边坡结构的失效概率Pf和对应可靠指标β.在计算上述Pf和对应β时,考虑了土体三个主要基本参数(重度γ、内摩擦角(Ψ)、粘聚力c)的随机特性.利用MATLAB程序的计算结果表明,随机变量对边坡可靠度的影响与基本随机参数对抗滑反力的贡献大小有关,即,贡献大的基本随机参数,它的随机波动对结构失效概率Pf的影响也较大,反之亦然.另外,基于MATLAB的算例计算结果还表明:边坡结构失效概率Pf对内摩擦角(Ψ)较敏感,而对重度y和粘聚力c次之.其次,当同时考虑三个随机变量的联合波动对Pf的影响时发现,当它们在小范围内随机波动时,其联合特性对Pf的影响较敏感,但当它们在大范围内随机波动时,Pf主要受敏感随机变量的影响,而三个随机变量联合作用对Pf的影响和敏感随机变量(Ψ)单独作用时相差不大.由此可见,在实际边坡工程可靠性分析中,土体内摩擦角起主要作用,不容忽视.(Based Bishop method and Monte Carlo method, using MATLAB programming software to calculate the failure probability Pf and the corresponding slope reliability index β structure in the calculation of the above Pf and the corresponding β, consider the three main basic soil parameters (severe γ internal friction angle (Ψ), cohesion c) of the random nature of calculation results using MATLAB program shows that the influence of random variables on the reliability of the basic random slope parameters against anti- slip contribution to the size of the force , that is , the contribution the basic parameters of large random , random fluctuations which affect the probability of structural failure Pf is also larger , and vice versa addition, the calculation based on MATLAB numerical results also show that : the structure of slope failure probability Pf internal friction angle (Ψ) more sensitive , while severe and cohesion c y followed . Secondly, when taking into account the impact of the joint fl)

Wavelet neural network time series prediction of short-term traffic flow forecasting

matlab code for boosting color in an image

鲁棒迭代学习控制的设计 　　对不确定时滞系统的基础 　　在性能指标(Robust iterative learning control design for uncertain time-delay systems based on a performance index)