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IEC_RMS_V0
This simple module calculate the RMS value of an input signal (also measured)by using the deffined equation in the IEC norm
- 2013-12-20 14:27:37下载
- 积分：1
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GSA
DG placement for reduction of power loss in power distribution system using GSA
- 2020-11-13 23:29:42下载
- 积分：1
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Matlab蚁群算法解决TSP问题代码超详细注释
说明： 启发因子，信息素的重要程度
期望因子，城市间距离的重要程度
信息素增强系数
蚂蚁数量
表示每条边的能见度
参数可修改(heuristic factor, the importance of pheromone
Expectation factor, the importance of distance between cities
Pheromone enhancement coefficient
Ant number
Indicates the visibility of each side
Parameters can be modified)
- 2021-01-20 18:18:10下载
- 积分：1
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chirp
对雷达系统中的常用LFM线性调频（chirp）信号及其匹配滤波器的设计进行MATLAB仿真(right of the radar system used LFM LFM (chirp) signals and matched filter into the design OK MATLAB)
- 2006-10-30 10:45:29下载
- 积分：1
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phasedifference
利用DFT实现两轮信号相位差计算，包含谐波信号污染，白噪声信号污染分析(Phase difference between two signals to achieve the use of DFT calculations, the signal containing harmonics pollution, contamination white noise signal analysis)
- 2013-12-09 12:06:24下载
- 积分：1
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tun_nh65
线性调频脉冲压缩的Matlab程序,包括广义互相关函数GCC时延估计，计算时间和二维直方图。( LFM pulse compression of the Matlab program, Including the generalized cross-correlation function GCC time delay estimation, Computing time and two-dimensional histogram.)
- 2017-03-25 12:08:50下载
- 积分：1
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Qfilters_point_detector
Quadrature filters point detector in scale-space
- 2010-03-14 21:02:13下载
- 积分：1
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radar-signal
自编比较全面的部分雷达信号编码，可自行修改使用，(Part of a more comprehensive self radar signal encoding, you can modify their own use,)
- 2014-10-29 15:44:26下载
- 积分：1
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ninghie_v21
模式识别中的bayes判别分析算法，进行逐步线性回归，小波包分析提取振动信号中的特征频率。( Pattern Recognition bayes discriminant analysis algorithm, Stepwise linear regression, Wavelet packet analysis to extract vibration signal characteristic frequency.)
- 2017-02-15 17:02:12下载
- 积分：1
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半监督分类算法
半监督学习(Semi-Supervised Learning，SSL)是模式识别和机器学习领域研究的重点问题，是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据，以及同时使用标记数据，来进行模式识别工作。当使用半监督学习时，将会要求尽量少的人员来从事工作，同时，又能够带来比较高的准确性，因此，半监督学习目前正越来越受到人们的重视。(Semi-Supervised Learning (SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method combining supervised learning with unsupervised learning. Semi-supervised learning uses a large number of unlabeled data, as well as labeled data, for pattern recognition. When using semi-supervised learning, it will require as few people as possible to work, and at the same time, it can bring relatively high accuracy. Therefore, semi-supervised learning is receiving more and more attention.)
- 2021-04-12 11:28:57下载
- 积分：1
