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GMSK
用matlab实现gmsk编码，可直接运行。(Using matlab to achieve GMSK encoding can be directly run.)
- 2009-01-02 18:40:45下载
- 积分：1
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quadetest
Dana Quade in 1979 proposed a test that is often more powerful than the Friedman test. It also eliminates block differences but weights the raw data indicate possibly more marked treatment effects. Whereas the Friedman test is basically an extension of the sign test, the Quade test is effectively an extension of the Wilcoxon signed rank test and is equivalent to it when the treatments are two.
- 2009-11-26 02:26:48下载
- 积分：1
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MATLAB_GUI_user
Matlab GUI编程中文参考手册，以及一些基本的程序介绍(Matlab GUI Programming Reference Manual, as well as some basic procedures for introduced)
- 2010-05-24 21:56:32下载
- 积分：1
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ardrone
四旋翼模型，通过使用matlab搭建的四旋翼模型(quadrotor model using simulink)
- 2013-03-04 19:58:56下载
- 积分：1
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rail
this pgm read text from file and encrypt using rail fence technique.Encrypted text written to file which is read and decrypted using railfence
- 2011-10-17 08:33:46下载
- 积分：1
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TDOA 定位算法chan实现
说明： tdoa 定位算法chan实现，输入三站坐标和左右时差即可解算出目标位置(Chan implementation of TDOA location algorithm)
- 2020-07-04 10:39:50下载
- 积分：1
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approx_entropy
calculate the approximate entropy of heart rate varibility
- 2010-09-06 16:36:58下载
- 积分：1
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wk
说明： 用于合成孔径雷达成像的wk算法,成像质量要优于距离多普勒算法及线性调频变标算法。(wk algorithm of synthetic aperture radar imaging)
- 2011-07-05 15:15:45下载
- 积分：1
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robotpathplanning
一种基于栅格法的移动机器人路径规划问题，可以自行改变障碍物位置坐标。(a robot path planning algorithm based on cell composition, you can change the position of obstacles. )
- 2020-07-15 09:38:50下载
- 积分：1
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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
