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EM_GM
％ 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
％( 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
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2010-Introduction-to-MATLAB
麻省理工学院的《matlab》学习的2010年课件资源，相当的不错，想学的不要错过，好难找的(MIT matlab learning courseware resources in 2010, quite good, want to learn not to be missed, so difficult to find)
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fmincon
Optimization of PID Parameters Using SIMULIN K and Optimization Toolbox
- 2019-05-23 08:15:20下载
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红外小目标检测matlab程序
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morden_communication_technology
基于MATLAB的现代通信技术仿真完整版！基于MATLAB的现代通信技术仿真完整版！(cdma simulation based on MATLAB(with matlab codes))
- 2010-06-08 10:56:20下载
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Introduction to Computers and Programming
using C++ and MATLAB
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1_
说明： 能够实现LMS滤波器的算法,实现LMS的仿真(LMS)
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harwav_packet
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ATC_Demo1
解析目标分解方法的程序，里面附带一个实例。具有指导意义(Program of Analytical Target casading with an example.)
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GABP神经网络
污水处理过程中关键水质参数无法在线监测的问题,提出基于PCA GABP神经网络的污水水质软测量方法。该方法由两部分组成:主元分析PCA和GABP神经网络。其中,GABP算法采用局部改进遗传算法优化神经网络权值,并采用自适应学习速率动量梯度下降算法对神经网络进行训练,建立软测量模型。仿真结果表明该软测量模型稳定性好、精度高,可用于污水处理厂对BOD进行在线预测。
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