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HPF
HIgh pass FIR filter. Can be applied to one dimensional signal.
- 2009-11-02 11:53:37下载
- 积分：1
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Vblast
vblast检测算法 OSIC算法，QPSK调制方式，生成BER图，有注释！(vblast detection algorithm OSIC algorithm, QPSK modulation, generate BER graph, comment!)
- 2015-04-09 10:38:19下载
- 积分：1
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pso-pso
说明： 一个用matlab编写的粒子群优化算法源程序(A written using matlab source PSO)
- 2011-03-27 00:57:30下载
- 积分：1
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no_grain_7_30
求解navier stokes equation的matlab代码(navier stokes
)
- 2012-08-02 17:24:12下载
- 积分：1
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Read_EH4_FileY_By_Matlab
EH4 Y 文件读取，用MATLAB编写(EH4 Y file read using MATLAB)
- 2012-06-29 14:12:46下载
- 积分：1
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MATLAB-with-matleb
Visual C++ 与Matlab混合编程，可以让Visual C++程序员快速进行matlab编程(Visual C++ with matleb combine pragraming )
- 2011-11-07 13:45:07下载
- 积分：1
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bpsbutt
带通/带阻巴特沃斯滤波器设计，采用IIR滤波器设计思路，可以返回数字滤波器的二阶分割形式(Band-pass/band-reject Butterworth filter design, using IIR filter design ideas, you can return to the form of digital filter second-order segmentation)
- 2010-01-13 13:48:31下载
- 积分：1
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capon
阵列信号处理中的capon算法，课本上的算法(Capon array signal processing algorithms, the algorithm textbook)
- 2021-04-28 14:48:43下载
- 积分：1
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OMP
一个很好的MATLAB源代码——OMP，OMP算法的改进之处在于：在分解的每一步对所选择的全部原子进行正交化处理，这使得在精度要求相同的情况下，OMP算法的收敛速度更快。(A good MATLAB source code-- OMP, OMP algorithm improvement lies in: every step of the decomposition of orthogonalization processing all of the selected atoms, which makes the accuracy requirement of the same circumstances, the OMP algorithm s convergence speed is faster.
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- 2013-08-24 12:51:20下载
- 积分：1
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knn1
K最邻近密度估计技术是一种分类方法，不是聚类方法。
不是最优方法，实践中比较流行。
通俗但不一定易懂的规则是：
1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。
2.选出最小的前K数据个距离，这里用到选择排序法。
3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method.
It is not the best method, but it is popular in practice.
Popular but not necessarily understandable rule is:
1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov).
2. select the minimum distance from the previous K data, where the choice sorting method is used.
3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)
- 2017-08-09 21:06:38下载
- 积分：1
