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Clustering_Coefficient
计算聚类系数和读相关系数的MATLAB,希望多多指教(Calculated clustering coefficient and time correlation coefficient of MATLAB, hope great weekend)
- 2010-07-28 21:31:57下载
- 积分：1
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k_means
一个简单的k-means分类方法，有详细的解释，能直接运行的。(A simple k-means classification method, and a detailed explanation can be run directly.)
- 2010-11-11 21:23:59下载
- 积分：1
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code
（1）用Doolittle三角分解（LU）法解方程组。
（2）分别用Jacobi迭代, Gauss-Seidel迭代法解方程组。
((1) Triangle Doolittle decomposition (LU) Solving equations. (2), respectively, with Jacobi iteration, Gauss-Seidel iteration method for solution of equations.)
- 2009-06-29 13:19:54下载
- 积分：1
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61738191-Satellite-Link-Budget-Analysis-Matlab-Co
satellite link budget analysis using matlab
- 2011-08-25 17:27:48下载
- 积分：1
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HAMED3
A tapered Bar Stiffeness & Displacement Matrix
- 2014-12-24 04:20:32下载
- 积分：1
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5.2.3
matlab源代码 基于MATLAB的Reed_Muller码编译码仿真(matlab source code based on MATLAB' s Reed_Muller decoding simulation)
- 2010-07-16 01:09:42下载
- 积分：1
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K-meanCluster
How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-element clusters
Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster.
Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample.
Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)
- 2007-11-15 01:49:03下载
- 积分：1
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motor
说明： 基于matlab/simulink环境，对异步电机的一个仿真，能够得到完整的仿真结果，是直接转矩控制的基础部分。(Based on matlab/simulink environment, a simulation of the induction motor, can be a complete simulation results, is a fundamental part of the direct torque control.)
- 2010-04-05 09:53:38下载
- 积分：1
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exprony_ma
求取系统特征模态,以及参数辨识使用。采用扩展的prony算法。(eigen value dentification)
- 2011-09-26 22:17:15下载
- 积分：1
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main
求二维点对问题，但是没有实现不知道怎么做？(the distans of some points )
- 2009-11-26 15:22:28下载
- 积分：1
