-
地震响应Matlab代码 odesolver
在matlab中利用odesolver进行单自由度有阻尼体系的时程分析，该代码使用时读入地震响应加速度（可为真实数据也可修改为理想函数），所有结构参数可调。输出加速度、速度和位移时程图像。(In the matlab in the use of odesolver single degree of freedom damping system of time history analysis, the code used to read the earthquake response acceleration (for real data can also be modified to the ideal function), all structural parameters adjustable. Output acceleration, speed and displacement time image.)
- 2020-12-08 20:29:20下载
- 积分：1
-
jibenrengongshichangfa
这是最基本的人工势场法，同时也做了很多注释，初始的是比较完美的数值仿真。但是，如果将注释中的语句与程序中的互换，就可以看到传统人工势场的缺陷。(
This is the basic artificial potential field, but also do a lot of notes, the initial value is more perfect simulation. However, if you comment statements and program exchange, we can see the shortcomings of traditional artificial potential field.)
- 2016-04-12 13:38:25下载
- 积分：1
-
Fresnel diffraction
给出不同情况下单缝菲涅尔衍射的光强分布图和灰度图(The intensity distribution and grayscale map of single Ja Faye Nel diffraction under different conditions are given.)
- 2018-01-15 18:13:20下载
- 积分：1
-
4
说明： iris recognition paper using func. in matlab
- 2010-10-19 04:09:59下载
- 积分：1
-
Artificial-Neural-Network-(ANN)-and-Fuzzy
Artificial Neural Network (ANN) and Fuzzy
- 2012-05-29 16:59:17下载
- 积分：1
-
zhangcalibration
经典的张正友的摄像机的两步标定程序，包括单目标定和立体标定程序。代码是基于matlab(Classic camera Zhang Zhengyou s two step calibration procedures, including single target and stereo calibration procedures. The code is based on the MATLAB)
- 2014-08-18 10:12:49下载
- 积分：1
-
matlab
matlab的介绍及其实例，很管用的哦，你不会失望的(matlab shili)
- 2012-04-28 20:12:39下载
- 积分：1
-
cannyedgedetection
基于canny边缘检测，模糊c均值聚类的图像分割(Canny edge detection based on fuzzy c-means clustering image segmentation)
- 2013-12-12 13:54:56下载
- 积分：1
-
High-Speed-modem
说明： 高速数据传输解调关键技术研究，大家可以好好学习一下(Modem high-speed data transfer key technologies, we can learn about)
- 2011-04-01 00:01:25下载
- 积分：1
-
matlab
聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)
- 2014-02-18 09:59:02下载
- 积分：1
