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attachments_2010_10_25
Vérification Méthode Media
- 2011-04-23 03:55:58下载
- 积分:1
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kummer
这个函数估计到库默尔与第N系列的广义超几何微分方程解的权力。库默尔的差分方程为:
x *的克 (十)+(二- X)的*克 ( x)的- A *的为g(x)= 0
该代码只有4线长,利用Matlab的向量运算有权采取了第N广义超几何级数的权力的总和。(This function estimates the solution to kummer s differential equation with the first N powers of the generalized hypergeometric series. Kummer s differential equation is given by:
x*g (x)+ (b- x)*g (x)- a*g(x) = 0
The code is just 4 lines long, using the power of Matlab s vector operations to take the sum over the first N powers of the generalized hypergeometric series.)
- 2011-05-23 12:33:21下载
- 积分:1
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direct-method-solve-linear-equation
基于MATLAB环境下的运用直接法求解线性方程组的对应的代码 简单易学 便于初学者消化使用(Based on MATLAB environment using a direct method for solving linear equations corresponding code is easy to learn for beginners to use digest)
- 2013-09-15 00:07:38下载
- 积分:1
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zuiyouhualilunyusuanfa-
国内节点优化算法书籍,内容丰富,算法齐全,实用性较强。定理的证明和算法的准导主要以数学分析和线性代数为基础,简明易学。(Domestic node optimization book, rich in content, the algorithm is complete, practical, strong. Theorems and algorithms quasi-proof guide mainly in mathematical analysis and linear algebra-based, concise and easy to learn.)
- 2013-11-25 21:45:05下载
- 积分:1
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qiyizhifenjie
奇异值分解降噪技术,对各种信号进行处理,使用先进的MATLAB程序进行分解处理,达到理想的效果(SVD noise reduction on various signal processing, the use of advanced decomposition MATLAB processing procedures to achieve the desired results)
- 2010-06-13 20:05:59下载
- 积分:1
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zigbee
zigbee files in matlab code
- 2010-10-15 14:34:23下载
- 积分:1
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FCMClust
数模资料。现在是聚类专题。这个是Cluster-FCM。刚刚运行完交的作业。(Digital to analog data. It is thematic clusters. This is the Cluster-FCM. Just finished running post jobs.)
- 2013-07-17 23:04:26下载
- 积分:1
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2DMUSIC
对阵列进行二维谱分析时使用,
用于信号估计,阵更信号处理(Spectral analysis of two-dimensional array used for signal estimation, array signal processing is more)
- 2011-06-12 11:17:18下载
- 积分:1
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tsp_dp1
traveler sale person in dynamic programming
- 2011-10-24 03:59:34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