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RadarSystemsAnalysisUsingMatlab
CFAR simulation matlab
- 2010-08-04 00:47:33下载
- 积分：1
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Wavelet_analysis_of_cases
汇集了大量的小波分析例子，详细的介绍小波分析的应用范围(Collection of a large number of examples of wavelet analysis, detail the scope of application of wavelet analysis)
- 2009-11-26 11:57:30下载
- 积分：1
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zuiyouhua
黄金分割法求极小，返回值fm为函数极小值，tm为极小值点，f为给定函数，t为函数变量，[a,b]为变量t的搜索区间(Golden section method is extremely small, the return value for the function fm minimum, tm for the minimum point, f for a given function, t for the function of variables, [a, b] for variable search interval t)
- 2008-12-23 21:21:56下载
- 积分：1
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four Toolbox for SVM
这里实现了基于四种SVM工具箱的分类与回归算法:
1、工具箱：LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱：OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱：stprtoolsvm
Classification_stprtool.m - 多类分类
4、工具箱：SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
更详细的相关函数说明请通过help命令查看！(Here the realization of the four SVM toolbox based on the classification and regression algorithm: 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox: stprtoolsvmClassification_stprtool.m- Multiclass Classification 4 toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting a more detailed explanation of the correlation function through the help command to view!)
- 2007-12-19 10:42:24下载
- 积分：1
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resconstruct
利用小波分解实现对信号多尺度分解重构，程序简单。(Wavelet decomposition of signal multi-scale decomposition and reconstruction, the program simple.)
- 2010-09-14 09:31:26下载
- 积分：1
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FDTD
电磁场与电磁波基于matlab的FDTD一维算法实现(Electromagnetic fields and electromagnetic waves matlab-based algorithm for one-dimensional FDTD)
- 2010-03-10 15:44:56下载
- 积分：1
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fdtd3D
三维光子晶体的fdtd法，MATLAB源程序 含不同时间步长的过程显示(Three-dimensional photonic crystals fdtd method, MATLAB source code)
- 2010-05-08 10:07:40下载
- 积分：1
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kmedian
The method works as follows.
1. For a data set with dimensionality, d, compute the variance
of data in each dimension (column).
2. Find the column with maximum variance call it cvmax
and sort it in any order.
3. Divide the data points of cvmax into K subsets, where K is
the desired number of clusters.
4. Find the median of each subset.
5. Use the corresponding data points (vectors) for each
median to initialize the cluster centers.
- 2013-08-10 03:45:31下载
- 积分：1
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Vinay-Project
LPRS using Edge detection and morphological operations
- 2013-11-24 20:39:48下载
- 积分：1
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lms
现代信号处理，语音处理，matlab程序，LMS算法(matlab lms speech)
- 2013-12-03 11:09:13下载
- 积分：1
