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LE
说明： 拉普拉斯特征映射算法，运用MATLAB编写完成。(Laplace feature mapping algorithm, using MATLAB prepared.)
- 2015-05-07 16:51:12下载
- 积分：1
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voice-yuputu
在matlab环境下实现，语谱图时间频率强度的图形描述。语谱图的实现(time frequent stronger)
- 2011-07-04 12:11:56下载
- 积分：1
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UGM
一个关于无向图推理模型的代码，可用于图像处理(An undirected graph inference on the model code)
- 2011-10-28 22:03:30下载
- 积分：1
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Fig6x1
直流驱动电机的matlab仿真文件，可以直接仿真结果(DC drive motor matlab simulation files, simulation results can be directly)
- 2014-01-20 17:14:02下载
- 积分：1
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cc1_matlab
信道编码的Matlab编程方法论文,英文版本(Channel coding of Matlab programming papers, the English version)
- 2010-02-12 11:50:57下载
- 积分：1
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med01-165
median filter details
- 2011-01-30 18:29:06下载
- 积分：1
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AttenuationOfwaveOnMatlab
安照标准格式给出数据信息excel文档，可以处理数据并形成可视化模型，包含原始excel文档与m文件(Security is given according to standard format data excel document, can handle data and develop visual models, including the original excel file documents and m)
- 2010-05-25 13:49:39下载
- 积分：1
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LMS
LMS算法实现自适应滤波
clear close all clc
N=10000 设置仿真长度
信号产生参数设定
a1=-0.195
a1=-1.5955
a2=0.95
R0=[1,a1,a2 a1,1+a2,0 a2,a1,1]
p=[1,0,0]
r=inv(R0)*p 计算理论自相关函数
R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵
p1=[r(2),r(3)] 生成互相关
h=inv(R)*p1 计算维纳解
Jmin=r(1)-h *p1 计算维纳解时最小均方误差
u=1/sum(eigs(R)) ( LMS算法实现自适应滤波
clear close all clc
N=10000 设置仿真长度
信号产生参数设定
a1=-0.195
a1=-1.5955
a2=0.95
R0=[1,a1,a2 a1,1+a2,0 a2,a1,1]
p=[1,0,0]
r=inv(R0)*p 计算理论自相关函数
R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵
p1=[r(2),r(3)] 生成互相关
h=inv(R)*p1 计算维纳解
Jmin=r(1)-h*p1 计算维纳解时最小均方误差
u=1/sum(eigs(R)) )
- 2021-03-01 22:29:34下载
- 积分：1
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turbo_en_and_decode
matlab仿真程序，有关信道编码中turbo码的编译码程序(matlab simulation program, the channel coding and decoding process in the turbo code)
- 2010-12-03 22:39:29下载
- 积分：1
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Multilabel-Image-Classification-via-High
Four crucial issues are considered by the proposed HoAL: 1) unlike binary cases, the selection granularity for multilabel active learning need to be fined from example to examplelabel pair 2) different labels are seldom independent, and label correlations provide critical information for efficient learning 3) in addition to pair-wise label correlations, high-order label correlations are also informative for multilabel active learning and 4) since the number of label combinations increases exponentially with respect to the number of labels, an efficient mining
method is required to discover informative label correlations
- 2014-09-03 02:03:47下载
- 积分：1
