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NeuralNetwork_BP
BP神经网络用于分类与回归的matlab源码
注释很详细(1、NeuralNetwork_BP_Classification.m- 分类
2、NeuralNetwork_BP_Regression.m- 回归
)
- 2010-01-07 14:54:01下载
- 积分：1
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figure_with_two_axis_with_same_grid
这个脚本绘制了两套相同的两个独立的轴具有相同的网格图上的1D数据。(This script plots two sets of 1D data on the same figure with two separate axis and with the same gridding. )
- 2011-08-25 21:12:04下载
- 积分：1
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lixiangjiaozheng
在不考虑运动误差的影响下，简单易懂的双基地前视sar距离徙动校正(Forward-looking, easy-to-understand bistatic the sar distance migration correction does not consider the impact of the motion error)
- 2013-04-15 11:09:37下载
- 积分：1
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information-rate
信息率失真函数的迭代计算，解决信息率失真的计算问题。(Iterative computation of information rate distortion function)
- 2012-05-07 14:36:28下载
- 积分：1
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matlab
matlab 从入门到精通，比较适合matlab初学者使用！希望对大家有所帮助！(matlab from entry to the master, more suitable for matlab beginners! We want to help!)
- 2009-11-19 19:04:40下载
- 积分：1
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mfcc
归一化倒谱提升窗口 预加重滤波器 语音信号分帧 计算每帧的MFCC参数 (Calculate the audio files of the MFCC factor)
- 2013-05-03 20:44:32下载
- 积分：1
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getEye
this is a matlab code that simulates gui motions
- 2017-05-13 13:11:47下载
- 积分：1
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MATLABtextdongtaiwenbenxianshi
是关于在MATLAB中动态显示文本的源代码，很有用的(With regard to dynamic display in the MATLAB version of the source code, very useful)
- 2009-04-21 21:46:37下载
- 积分：1
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BP5
利用BP神经网络识别字母，选用改进的BP算法，精度高，抗噪声能力好(BP neural network using the letters, use the improved BP algorithm, high precision, good noise immunity)
- 2011-01-20 11:04:54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)
％
％ 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
