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01_introduction
presentation of MATLAB
- 2009-05-26 23:30:40下载
- 积分：1
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AmbiguityFun
画雷达信号的模糊函数，包括单脉冲信号、线性调频信号。(The painting of the ambiguity function of radar signals, including the single-pulse signal, linear frequency modulation signal.)
- 2012-05-05 10:46:35下载
- 积分：1
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DampedEfieldTool
a damping gui source code
- 2014-09-17 10:15:15下载
- 积分：1
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OneStepUKF
卡尔曼滤波器，扩展卡尔曼滤波器，无味卡尔曼滤波器实现，对比(Kalman filter, extended Kalman filter, unscented Kalman filter implementation, compared to)
- 2013-09-30 16:27:43下载
- 积分：1
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sine_wave_generation
a matlab simulink simulation for sine wave generation
- 2014-09-11 14:01:27下载
- 积分：1
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press
matlab simulink PID 大迟延对象控制模型(Time Delay matlab simulink PID control model)
- 2014-01-17 10:18:26下载
- 积分：1
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cfar
MATLAB雷达检测CFAR.这是CA-CFAR程序。里面包含所需要的函数和数据文件。(This is simple cell-averaging lead/lag CFAR.)
- 2021-04-27 13:58:45下载
- 积分：1
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Lag_Newton
用MATLAB编写的一个数值分析中，利用拉格朗日和牛顿迭代求解(a way of solving the method of larg and
Newton)
- 2010-01-24 17:01:17下载
- 积分：1
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fengwoxiaoqu
多小区、多用户蜂窝小区的建模。其中每个小区内设置一个基站，以基站为圆心，以一定半径在基站附件分布n个用户。可直接运行。(Multi-cell, multi-user cell modeling. Which sets a base station within each cell, the base station as the center, the distribution of n users to a certain radius of the base station attachment. Can be run directly.)
- 2021-01-31 17:18:32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
