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l1-magic的matlab代码
l1-magic的matlab代码,l1-magic: Recovery of Sparse Signals
via Convex Programming(l1-magic of matlab code, l1-magic: Recovery of Sparse Signalsvia Convex Programming)
- 2007-10-28 17:47:41下载
- 积分:1
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HarmElimination
By the harmonic elimination technique,we can solve for the switching angles of a half bridge to cancel the 5th, 7th, 11th and 13th harmonics by the Newton Raphson iteration technique.
- 2011-06-19 01:36:15下载
- 积分:1
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simulatiion
simulation of an arm on matlab
- 2013-07-11 17:13:30下载
- 积分:1
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power_Transfo3phCoreType
power_Transfo3phCoreType.rar,功率电子领域matlab仿真文件,已经验证过,程序运行正常(power_Transfo3phCoreType.rar,
Power electronics field matlab simulation file, has already been verified, the normal operating procedures)
- 2013-08-26 22:00:01下载
- 积分:1
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PDC-analysis
利用偏直接一致(PDC)指数分析同步采集的脑电信号和肌电信号之间的信息传递方向
(Analysis the information transfer direction btween synchronous EEG and EMG
)
- 2013-03-12 19:23:42下载
- 积分:1
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ntirvfqy
能量熵的计算,包含特征值与特征向量的提取、训练样本以及最后的识别,含噪脉冲信号进行相关检测,有循环检测,周期性检测,IDW距离反比加权方法,在matlab环境中自动识别连通区域的大小。( Energy entropy calculation, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Noisy pulse correlation detection signal, There are cycle detection, periodic testing, IDW inverse distance weighting method, Automatic identification in the matlab environment the size of the connected area.)
- 2016-03-07 21:31:19下载
- 积分:1
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PDFofQuess
高斯独立同分布的mimo信道环境下,对协方差矩阵R的个元素的概率密度函数的统计(PDF of R under Quess Channel)
- 2009-11-06 23:04:45下载
- 积分:1
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particle_filter
particle filter in matlab
- 2015-01-06 06:09:30下载
- 积分:1
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ssxsjPSO
实数编码的小生境PSO算法优化多模态函数(Real-coded niche PSO algorithm for multimodal function optimization)
- 2013-11-13 11:53:07下载
- 积分:1
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a
说明: 基于密度的聚类算法因其抗噪声能力强和能发现任意形状的簇等优点,在聚类分析中被广泛采用,本文提出
的基于相对密度的聚类算法,在继承上述优点的基础上。有效地解决了基于密度的聚类结果对参数值过于敏感、参数
值难以设置以厦高密度簇完全被相连的低密度簇所包含等问题。(Density-based clustering algorithm because of its strong resistance to noise and can find clusters of arbitrary shape, etc., in the cluster analysis is widely used, the proposed clustering algorithm based on the relative density, in succession on the basis of the above-mentioned advantages. Effectively solve the density-based clustering results on the parameter value is too sensitive, difficult to set the parameter value to high-density clusters of buildings connected to the low-density clusters are completely contained and other issues.)
- 2010-12-06 16:31:17下载
- 积分:1