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c2948_pdf_toc
matlab教程（英文） matlab教程（英文） matlab教程（英文） matlab教程（英文） matlab教程（英文） (matlab tutorial (English) matlab Tutorial (English) matlab Tutorial (English) matlab Tutorial (English) matlab Tutorial (English))
- 2007-08-15 03:17:30下载
- 积分：1
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jpeg
整理的一些JPEG实现图像编解码的程序，已matlab实现(some image encoding and decoding procedures based on JPEG)
- 2010-11-09 20:02:57下载
- 积分：1
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PSORT20110515i
matlab code for pso
Particle Swarm Optimization Research Toolbox
- 2011-07-05 18:53:55下载
- 积分：1
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peakfit
峰值滤波用于数据特征处理，可提高算法运算速度和鲁棒性(Peak filter characteristics for data processing, the operation speed can be increased and the robustness of the algorithm)
- 2014-12-10 17:24:35下载
- 积分：1
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Fibermodes
计算光纤模量的MatLab源码，需要输入折射率，芯径比，模式等参数。(Calculation of fiber modulus MatLab source code, need to enter the refractive index, core diameter ratio, the mode parameter.)
- 2007-11-15 02:13:10下载
- 积分：1
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MTLAB
讲解如何使用Matlab进行建模与仿真，并对仿真结果进行分析和可视化(Explain how to use Matlab for modeling and simulation, and simulation results for analysis and visualization)
- 2008-01-26 20:14:24下载
- 积分：1
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LFM
线性调频信号雷达脉冲压缩仿真及程序，chirp信号的产生，压缩及效果(LFM singal simulation)
- 2021-04-12 16:48:56下载
- 积分：1
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qianru
通过在语音信号中嵌入鲁棒性水印和脆弱性水印，实现对数据的版权保护。(Embedded in the speech signal through robust watermarking and fragile watermarking, copyright protection to achieve the data.)
- 2010-06-12 21:40:45下载
- 积分：1
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fs_sup_relieff
Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重：
如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules:
If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)
- 2018-04-17 14:41:55下载
- 积分：1
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speceffi
To Calculate the Spectral efficiency of a continuous-time AWGN Channel in bits/s/Hz
- 2015-03-20 22:16:11下载
- 积分：1
