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Description: 此源码为设计csd码的matlab原程序，可以实现十进制或二进制补码与csd码的互换，工程实现中减少了自己编程转换的工作量
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Size: 2766 |
Author: 骆军 |
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Description: ex6_1 ～ ex6_3二项分布的随机数据的产生
ex6_4 ～ ex6_6通用函数计算概率密度函数值
ex6_7 ～ ex6_20常见分布的密度函数
ex6_21 ～ ex6_33随机变量的数字特征
ex6_34 采用periodogram函数来计算功率谱
ex6_35 利用FFT直接法计算上面噪声信号的功率谱
ex6_36 利用间接法重新计算上例中噪声信号的功率谱
ex6_37 采用tfe函数来进行系统的辨识，并与理想结果进行比较
ex6_38 在置信度为0.95的区间上估计有色噪声x的PSD
ex6_39 在置信度为0.95的区间上估计两个有色噪声x，y之间的CSD
ex6_40 用程序代码来实现Welch方法的功率谱估计
ex6_41 用Welch方法进行PSD估计，并比较当采用不同窗函数时的结果
ex6_42 用Yule-Walker AR法进行PSD估计
ex6_43 用Burg算法计算AR模型的参数
ex6_44 用Burg法PSD估计
ex6_45 比较协方差方法与改进的协方差方法在功率谱估计中的效果
ex6_46 用Multitaper法进行PSD估计
ex6_47 用MUSIC法进行PSD估计
ex6_48 用特征向量法进行PSD估计-ex6_1 ~ ex6_3 binomial distribution of the generated random data
ex6_4 ~ ex6_6 generic function value of the probability density function
ex6_7 ~ ex6_20 common distribution density function
ex6_21 ~ ex6_33 figure characteristics of random variables
periodogram function ex6_34 used to calculate the power spectrum
ex6_35 direct method using FFT signal above the noise of the power spectrum
ex6_36 recalculated using the indirect method on the example of the power spectrum of noise signal
tfe function ex6_37 used for system identification, and results were compared with the ideal
ex6_38 at 0.95 confidence interval for the estimated colored noise x on the PSD
ex6_39 at 0.95 confidence interval of the two colored noise on the estimated x, y between the CSD
ex6_40 code used to achieve the Welch method of power spectrum estimation
Welch method ex6_41 with PSD estimates, and compare different window function when the results when
ex6_42 using Yule-Walker AR method is esti
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Size: 7168 |
Author: 张满超 |
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Description: 图模型（Graphical Model）,加州大学柏克利计算机系、统计系教授，Jordan的技术报告，适合于机器学习、概率统计、贝叶斯网络等的研究-Graphical Model, University of California at Berkeley ,Dept. of computer science, Dept. of statistics, Professor Jordan s technical report, suitable for machine learning, probability and statistics, Bayesian networks, etc
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Size: 370688 |
Author: yism |
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Description: Semi-automatic Differentiation (SD) Toolkit is a Matlab implementation
of the complex step derivative (CSD) technique for the differentiation of real-valued functions. The Toolkit consists of three core functions:
sdGrad.m - Returns CSD approximation of the gradient (g) of the
scalar-valued target function fun(p,Extra), according to Equation 3
of the paper.
sdJac.m - Returns CSD approximation of the Jacobian (J) of the
scalar-valued target function fun(p,Extra), according to Equation 3
of the paper.
sdHg.m - Rerurns CSD approximation of the Hessian (H) of the
scalar-valued target function fun(p,Extra), according to Equation 7 of the
paper. It also returns the centered-difference CSD approximation of the
gradient as a by-product.
For a brief describtion of the functions in the toolkit,
type ,help sdToolkit> at Matlab command prompt.-The sdToolkit demonstrates the complex step derivative method on a variety of functions and geophysically oriented examples
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Size: 28672 |
Author: 蒋礼 |
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Description: 采用CSD编码的常系数乘法器的FIR滤波器的设计。-CSD-coded using constant coefficient multipliers of the FIR filter design.
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Size: 9216 |
Author: 敬礼 |
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Description: Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Sequential Floating Backward Selection (SFBS)
• ReliefF
Two CCR estimation methods:
• Cross-validation
• Resubstitution
After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.
Figure: Upper panel is the pattern x feature matrix
Lower panel left are the features selected
Lower panel right is the CCR curve during feature selection steps
Right panel is the classification results of some patterns.
This software was developed using Matlab 7.5 and Windows XP.
Copyright: D. Ververidis and C.Kotropoulos
AIIA Lab, Thessaloniki, Greece,
jimver@aiia.csd.auth.gr
costas@aiia.csd.auth.gr-Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Sequential Floating Backward Selection (SFBS)
• ReliefF
Two CCR estimation methods:
• Cross-validation
• Resubstitution
After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.
Figure: Upper panel is the pattern x feature matrix
Lower panel left are the features selected
Lower panel right is the CCR curve during feature selection steps
Right panel is the classification results of some patterns.
This software was developed using Matlab 7.5 and Windows XP.
Copyright: D. Ververidis and C.Kotropoulos
AIIA Lab, Thessaloniki, Greece,
jimver@aiia.csd.auth.gr
costas@aiia.csd.auth.gr
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Size: 3283968 |
Author: driftinwind |
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Description: 基于FPGA的CSD编码乘法器（在MATLAB环境中）-FPGA-based multipliers CSD code (in MATLAB environment)
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Size: 80896 |
Author: xiaoyuehaome |
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Description: 在MATLAB程序中利用FDATOOL工具得到系数，然后由此十进制系数生成CSD码-In the MATLAB program by using FDATOOL tools coefficient, then the resulting decimal CSD code coefficients generated
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Size: 5120 |
Author: xiaoyuehaome |
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Description: 基于CSD编码的FIR数字滤波器优化设计（使用MATLAB程序）-CSD coding based FIR digital filter design (using the MATLAB program)
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Size: 264192 |
Author: xiaoyuehaome |
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Description: 二进制转成CSD编码的Matlab程序，只要运行就可以实现-CSD code convert binary Matlab program can be achieved as long as the running
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Size: 2048 |
Author: jinglili |
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Description: Welch功率谱密度是用改进的平均周期图法来求取随机信号的功率谱密度估计值。Welch法采用信号重叠分段、加窗函数和FFT算法等计算一个信号序列的自功率谱估计(PSD如上例中的下半部分的求法)和两个信号序列的互功率谱估计（CSD）。MATLAB信号处理工具箱函数提供了专门的函数PSD和CSD自动实现Welch法估计，而不需要自己编程。-method of power spectral density plot
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Size: 2048 |
Author: LinkedBox |
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Description: 复球解码算法的MATLAB实现,其实现环境为MIMO多天线仿真环境。-complex sphere decoder
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Size: 6144 |
Author: 凌厉 |
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Description: matlab's CSD toolbox
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Size: 43008 |
Author: DAngelo
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Description: CSD编码的高效MATLAB 算法模型(An efficient MATLAB algorithm model based on CSD encoding)
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Size: 1024 |
Author: vwan
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