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Matlab_typical_examples
对于matlab初学者一些很好的例子，里面有详细的求解过程和matlab代码可供复制编译。(Matlab beginners for some good examples, there are detailed solving process and compile matlab code for replication.)
- 2009-01-01 15:01:46下载
- 积分：1
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MATLABpaidui
用matlab进行排队论仿真的经典论文，有兴趣的同学可以参考一下。(Matlab simulation carried out with the classic queuing theory papers, students who are interested can refer to.)
- 2010-08-29 10:52:15下载
- 积分：1
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BLIND-SOURCE-SEPARATION
BLIND SOURCE SEPARATION
- 2013-10-31 08:15:30下载
- 积分：1
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WTWPTour
WTWPTour function in wavelet processing
- 2013-05-08 01:21:00下载
- 积分：1
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mobileuwbcomm
The function of channel estimation is to form an estimate of the amplitude
- 2010-08-13 13:51:36下载
- 积分：1
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matlab-huidu-yuce
基于matlab的灰色预测的代码大全，能够实现不同的灰度预测结果，有利于初学者对灰度预测的把握，有利于学习练习和应用(Different gray forecast results can be achieved based on gray prediction matlab code Daquan, help beginners grasp grayscale forecast is conducive to learning exercises and applications)
- 2013-01-10 12:53:19下载
- 积分：1
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files
many progrem used in digital communiction
- 2013-05-16 05:25:16下载
- 积分：1
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Zfenxi
离散系统Z域分析
实验步骤：
主界面下进入实验六的“离散系统Z域分析”，输入分子多项式的系数向量
按照 z 降幂的顺序输入，如：，输入为。
输入分母多项式的系数向量，按照 z 降幂的顺序输入。
鼠标单击确定按钮，显示系统函数的幅频特性曲线，相频特性曲线。(Z-domain analysis of discrete-time systems experimental steps: the main interface into the six experiments the " Z-domain analysis of discrete-time systems" , enter the coefficient of polynomial vector elements z in accordance with the descending order of power input, such as:, input. Denominator polynomial coefficients input vector, z in accordance with the order of descending input power. Mouse click OK button, and display system function curve of amplitude-frequency characteristics, phase-frequency characteristic curve.)
- 2009-05-01 20:37:37下载
- 积分：1
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FFT
描述的是一个关于快速傅里叶变化的仿真，这是在一个图上描述两个图形。(Describes a simulation on the fast Fourier transform, which is described in a graph of two graphs.)
- 2011-01-06 13:45:12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
