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MATLAB
matlab系统仿真的说明，例子多样清楚，简单易懂(system simulation matlab note, for example, clearly diverse, easy-to-read)
- 2009-03-26 13:44:00下载
- 积分：1
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PCA_GUI_code
主成分析matlab图形用户界面代码，包含测试文件。(principal component analysis matlab gui code. test file included.)
- 2009-10-25 09:57:26下载
- 积分：1
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longerkuta
用于四阶龙格库塔数值积分，做matlab仿真实验时会用到。(For the fourth-order Runge-Kutta numerical integration, doing matlab simulation experiments will be used. )
- 2012-03-24 17:09:59下载
- 积分：1
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matlab-Create-Read-Update-Delete-database-lp2m-ar
how you can create, read, delete and update using Matlab by simple code
- 2014-11-07 06:24:55下载
- 积分：1
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optics-simulation
高等光学仿真原程序，里面有光纤波导激光原理等(Advanced optics simulation of the original program, which has fiber waveguide laser principle, etc.)
- 2013-10-30 19:10:51下载
- 积分：1
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BerBeamforming
Ber using beamforming sourcecode matlab
- 2015-03-05 23:59:54下载
- 积分：1
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Lagrangian multiplier method
通过matlab实现拉格朗日乘子法。学习经典优化方法，熟悉matlab语言。(Realize the Lagrangian multiplier method by matlab. Learning classic optimization methods, familiar with matlab language.)
- 2021-04-08 13:19:01下载
- 积分：1
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readMNIST
用ELM实现手写数字的识别，快速，用MNIST数据库(Handwritten numbers recognition realized by ELM)
- 2017-06-16 15:10:17下载
- 积分：1
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HPCGettingStarted
Windows HPC Server 2008 Getting Started Guide
- 2010-09-20 04:31:48下载
- 积分：1
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EM_GM
％ EM algorithm for k multidimensional Gaussian mixture estimation
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％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components allowed
％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
％ maxiter - maximum number of iteration allowed ([] for none)
％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
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％ Ouputs:
％ W(1,k) - estimated weights of GM
％ M(d,k) - estimated mean vectors of GM
％ V(d,d,k) - estimated covariance matrices of GM
％ L - log likelihood of estimates
％( EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates)
- 2008-04-27 15:51:27下载
- 积分：1
