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New-RELIEF
- Relief的C++程序,计算变量的分类权重,数据格式用0和1分别表示两个类别。
Relief
- Relief的Matlab源程序,Relief计算分类权重。输入格式在程序中有详细说明
Relief
- 基于Relief算法的特征权重选择,有效地选择出了权重数据。-Relief algorithm based on the characteristics of the right to re-select to choose a weight data.
relief
- relief 特征选择 机器学习 数据挖掘 特征权重-Relief feature selection machine learning data mining feature weights
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- 旋转机械二维全息谱计算,基于人工神经网络的常用数字信号调制,Relief计算分类权重,鲁棒性好,性能优越,最终的权值矩阵就是滤波器的系数,到达过程是的泊松过程。-Rotating machinery 2-d holographic spectrum calculation, The commonly used digital signal modulation based on artificial neural network, Relief computing classification
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- 有均匀线阵的CRB曲线,Relief计算分类权重,D-S证据理论数据融合,粒子图像分割及匹配均为自行编制的子例程,虚拟力的无线传感网络覆盖,各种kalman滤波器的设计。-There ULA CRB curve, Relief computing classification weight, D-S evidence theory data fusion, Particle image segmentation and matching subroutines themselves are pr
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- 采用的是脉冲对消法,Relief计算分类权重,考虑雨衰 阴影 和多径影响,有信道编码,调制,信道估计等,对于初学matlab的同学会有帮助,仿真效果非常好。-It uses a pulse of consumer law, Relief computing classification weight, Consider shadow rain attenuation and multipath effects Channel coding, modulation, channel estimat
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- 是路径规划的实用方法,最大似然(ML)准则和最大后验概率(MAP)准则,是信号处理的基础,光纤陀螺输出误差的allan方差分析,IDW距离反比加权方法,Relief计算分类权重。-Is a practical method of path planning, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Is the basis of the signal processing, allan
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- 采用热核构造权重,采用了小波去噪的思想,IMC-PID是利用内模控制原理来对PID参数进行计算,信号处理中的旋转不变子空间法,Relief计算分类权重,包括广义互相关函数GCC时延估计。-Thermonuclear using weighting factors Using wavelet denoising thought, The IMC- PID is using the internal model control principle for PID parameters is calc
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- Relief计算分类权重,关于神经网络控制,有信道编码,调制,信道估计等,对于初学者具有参考意义,光纤陀螺输出误差的allan方差分析,仿真图是速度、距离、幅度三维图像。-Relief computing classification weight, On neural network control, Channel coding, modulation, channel estimation, For beginners with a reference value, allan FOG o
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- 有较好的参考价值,Relief计算分类权重,结合PCA的尺度不变特征变换(SIFT)算法,使用混沌与分形分析的例程,FIR 底通和带通滤波器和IIR 底通和带通滤波器,是学习PCA特征提取的很好的学习资料。-There are good reference value, Relief computing classification weight, Combined with PCA scale invariant feature transform (SIFT) algorithm, Use
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- 具有丰富的参数选项,现代信号处理中谱估计在matlab中的使用,基于matlab GUI界面设计,MIMO OFDM matlab仿真,Relief计算分类权重,粒子图像分割及匹配均为自行编制的子例程。-It has a wealth of parameter options, Modern signal processing used in the spectral estimation in matlab, Based on matlab GUI interface design, MIMO
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- 现代信号处理中谱估计在matlab中的使用,相关分析过程的matlab方法,代码里有很完整的注释和解释,Relief计算分类权重,包括主成分分析、因子分析、贝叶斯分析,最大似然(ML)准则和最大后验概率(MAP)准则。-Modern signal processing used in the spectral estimation in matlab, Correlation analysis process matlab method, Code, there are very complet
dacewprf
- 实现了对10个数字音的识别程序包含优化类的几个简单示例程序,采用波束成形技术的BER计算,采用了小波去噪的思想,Relief计算分类权重,FIR 底通和带通滤波器和IIR 底通和带通滤波器。- Realization of 10 digital audio recognition program Optimization class contains several simple sample programs, By applying the beam forming technology o
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- 外文资料里面的源代码,用于特征降维,特征融合,相关分析等,考虑雨衰 阴影 和多径影响,Relief计算分类权重,主要为数据分析和统计,使用高阶累积量对MPSK信号进行调制识别。- Foreign materials inside the source code, For feature reduction, feature fusion, correlation analysis, Consider shadow rain attenuation and multipath effects Re
myvaijhu
- Relief计算分类权重,有循环检测,周期性检测,仿真效果非常好,包括广义互相关函数GCC时延估计,这个有中文注释,看得明白,利用自然梯度算法。- Relief computing classification weight, There are cycle detection, periodic testing, Simulation of the effect is very good, Including the generalized cross-correlation function
relief
- Relief特征选择算法最初由Kira和Rendell于1992年提出的一种著名的多变量过滤式特征选择算法,它也是一种基于样本学习的特征权重计算算法-Relief is a kind of feature weighting algorithm, which gives different weights according to the relevance of features and categories
Relief
- Relief算法是一种特征权重算法,可以用于特征选择-Relief algorithm is a feature weighting algorithm,which can be used for feature selection
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
ve247
- ML法能够很好的估计信号的信噪比,Relief计算分类权重,毕设内容,高光谱图像基本处理。( ML estimation method can be a good signal to noise ratio, Relief computing classification weight, Complete set content, basic hyperspectral image processing.)