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Gaussc
选主元的高斯消元法，用于求解线性方程组。很方便！基于c++开发。(Selected principal component of the Gaussian elimination method for solving linear equations. Very convenient! Based on c++ development.)
- 2010-03-03 10:41:17下载
- 积分：1
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SAMP
压缩感知中的稀疏度自适应算法，针对稀疏度未知的情况进行迭代(sparsity adaptive matching pursuit)
- 2021-04-18 12:38:52下载
- 积分：1
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zhaoxiaopu
位置指令为幅值为1.0的阶跃信号，r（k）=1.0。网络结构为1-4-1，高斯函数的参数值取Cj=[-2 -1 1 2]T ，B=[0.5 0.5 0.5 0.5]T 。
网络权值学习参数为η=0.30，α=0.05 。PID控制各参数的初RBF网络控制，被控对象为G（s）=
取采样时间为1ms，采用Z变换进行离散化，离散化后的被控对象为
y(k)=-den(2)*y（k-1）-den(3)*y(k-2)+num(2)*u(k-1)+num(3)*u(k-2)
始值为，kp=20， kd=0.3， ki=0.1。
(Position command for the step signal amplitude of 1.0, r (k) = 1.0. The network structure is 1-4-1, the Gaussian function parameters taken Cj = [-2-1 1 2] T, B = [0.5 0.5 0.5 0.5] T. Weight learning parameter η = 0.30, α = 0.05. PID control parameters at the beginning of each RBF network control, the controlled object is G (s) = take the sampling time is 1ms, using the Z transform discrete, discretized controlled object is y (k) =-den (2)* y (k-1)-den (3)* y (k-2)+num (2)* u (k-1)+num (3)* u (k-2) initial value, kp = 20, kd = 0.3, ki = 0.1.)
- 2013-07-22 21:20:28下载
- 积分：1
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Matlab1
适合MATLAB初学者，有关符号说明部分，可以更快掌握一门语言(MATLAB for beginners, the relevant symbol Description section, you can quickly master a language)
- 2014-11-09 16:29:35下载
- 积分：1
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Delete-File-System-Minifilter-Driver
Delete File System Minifilter Driver
- 2014-12-07 15:56:58下载
- 积分：1
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uwb
ppt on basic understanding of uwb antenna and uwb antenna design for under water communication
- 2015-02-05 02:37:12下载
- 积分：1
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coherence
功率谱和相干性计算的原理和matlab实现，比较经典的一篇文献，适合算法的研究者参考。来自BMSP The power spectrum and coherence function。(Principles and matlab power spectrum and coherence computing a reality, a more classic literature, researchers algorithm for reference. From BMSP The power spectrum and coherence function.)
- 2016-02-22 00:51:45下载
- 积分：1
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GSF
基于GSF方法的潮流计算，MATLAB程序，故障预算，case30(GSF method based on flow calculation, MATLAB programs, fault the budget, case30)
- 2010-03-01 10:09:26下载
- 积分：1
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10721582R1
采用稀疏表示能够实现N类M个人脸的正常识别(Using sparse representation can be achieved Class N M individual normal face recognition)
- 2012-05-20 22:28:59下载
- 积分：1
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TPretroPropag
Artificial Intellegence: backpropagation
- 2012-05-08 19:12:46下载
- 积分：1
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