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jsscx1
近似熵MATLAB的计算程序，可以通过此程序对脑电信号EEG进行分析，达到你要的结果。程序仅供参考，里面可能有少许不足之处，希望大家不吝赐教。(approximate entropy MATLAB program, through this procedure right EEG EEG analysis you want to achieve results. Procedures for reference purposes only, which may have some shortcomings, we hope that substantive progress has spared no.)
- 2007-05-11 10:06:13下载
- 积分：1
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msfuntmpl
this is file for traffic networks benchmarks...
- 2013-03-11 15:37:01下载
- 积分：1
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matlab
基于matlab的图像压缩的程序，改变不同的QF得到不同的压缩图像(compact picture)
- 2010-01-17 20:16:46下载
- 积分：1
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t
说明： The anisotropic diffusion
filter is formulated as a process that enhances object boundaries
by performing intra-region as opposed to inter-region
smoothing
- 2011-09-23 20:48:38下载
- 积分：1
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MachineLearning
MachineLearning
Classifican
KNN-Based Clustering for Improving Social
Recommender Systems
- 2014-01-31 00:59:11下载
- 积分：1
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test1
递归实现一个集合的所有的子集的输出。
例如{1，2}
输出{}{1}{2}{1，2}(A subset of the output of recursion)
- 2010-01-10 00:16:28下载
- 积分：1
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bpsk
bpsk modulation in matlab
- 2009-07-15 11:05:34下载
- 积分：1
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MATLAB-GUI
MATLAB GUI实现动态画图曲线的源程序代码 具有完整的代码和运行结果(MATLAB GUI dynamically draw the curve of the source code)
- 2014-12-17 19:52:31下载
- 积分：1
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sixthcharpter
《精通MATLAB与C/C++混合程序设计》刘维第二版( Proficient in MATLAB and C/C++ mixed programming design second edition of Liu Wei)
- 2015-04-10 22:00:12下载
- 积分：1
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MyKmeans
实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))
- 2005-07-26 01:32:58下载
- 积分：1
