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Jacobi
说明： Jacobi的matlab程序是我同学编着玩的，我试了一下挺好，Jacobi迭代算法。(Jacobi s matlab program is edited by students, I play, I tried some very good, Jacobi iterative algorithm.)
- 2008-11-19 11:36:37下载
- 积分：1
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Untitled2
此代码程序是用来计算kolmogorov的，很便捷使用。谢谢(This code program is used to calculate kolmogorov, it is convenient to use.Thank you)
- 2012-04-19 22:33:26下载
- 积分：1
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ASTFT-WVD
短时傅立叶变换与魏格纳威尔分部相结合的时频分析算法以及自适应短时傅立叶变换( U77ED u65F6 u5085 u7ACB u53F6 u53D8 u6362 u4E0E u9B4F u683C u7EB3 u5A01 u5C14 u5206 u90E8 u76F8 u7ED3 u5408 u7684 u65F6 u9891 u5206 u6790 u7B97 u6CD5 u4EE5 u53CA u81EA u9002 u5E94 u77ED u65F6 u5085 u7ACB u53F6 u53D8 u6362)
- 2020-11-30 15:49:27下载
- 积分：1
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APcode
聚类代码(include sparse capability)(Clustering code (include sparse capability))
- 2010-09-06 11:05:42下载
- 积分：1
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small_signal_9009301
this is a very good mfile for small signal analyze
- 2012-06-02 03:01:21下载
- 积分：1
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FFT
在matlab环境下编写自己的fft算法，与系统的函数进行对比分析(In the matlab environment to write your own fft algorithm, and a comparative analysis of the system function)
- 2011-11-17 19:39:01下载
- 积分：1
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huffman
source code for huffman
- 2015-02-09 17:32:30下载
- 积分：1
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DSM_AGC
用DSM调制1-bit输出，经简单模拟滤波电路，产生VGA控制电压。对于内部频率高、但VGA变化速度较慢的场合，可以达到很高的控制精度，从而省却了内部高精度DAC的模块(DSM modulation with 1-bit output, through a simple analog filter circuit, producing VGA control voltage. in the circumstance of high internal frequency, but need a slower changing VGA control, this program can achieve high control precision, and thus save the internal high-accuracy DAC module)
- 2011-12-01 11:20:40下载
- 积分：1
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parallel_chebysheve_coffi
计算平行线耦合的奇偶模阻抗值和切比雪夫低通原型滤波器的耦合系数(caculate the parrellel coupleline odd and even resistance value and based on the Chebyshev lowpassfilter coupled cofficients)
- 2014-07-27 21:23:01下载
- 积分：1
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HDFaceRecognitionSystemMatlabsourcecode
Advances in data collection and storage capabilities during the past decades have led to an information overload in most sciences. Researchers working in domains as diverse as engineering, astronomy, biology, remote sensing, economics, and consumer transactions, face larger and larger observations and simulations on a daily basis. Such datasets, in contrast with smaller, more traditional datasets that have been studied extensively in the past, present new challenges in data analysis. Traditional statistical methods break down partly because of the increase in the number of observations, but mostly because of the increase in the number of variables associated with each observation. The dimension of the data is the number of variables that are measured on each observation.
- 2009-07-11 13:58:55下载
- 积分：1
