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Description: EMD2007年5月最新程序，是法国人做出来的，对大家使用EMD非常有好处的-EMD2007 May, the latest procedures, the French do it. Members of the use of EMD very good
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Author: 张楠 |
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Description: S变换 C语言程序 由R.G.Stockwell 编写
包含了正反变换 以及希尔伯特变换正反变换-S transform C language program prepared by the RGStockwell contains both positive and negative Hilbert transform, as well as positive and negative change
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Author: D.mk |
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Description: 站长,这是我看到你关于EMD在图像压缩方面最经典的一篇文章,国内所有关于EMD在图像压缩方面的论文都是从这篇论文上来的,请站长查收.-Station, which is what I see you on the EMD in the most classical image compression an article on the EMD in all aspects of image compression papers are up from this paper, please check station.
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Author: 向南 |
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Description: 一个法国人的Matlab EMD程序，包括例程，分享给大家。-A French Matlab EMD procedures, including routines, to others.
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Author: 王辉 |
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Description: EMD的Toolbox及使用方法
经验模态分解（Empirical Mode Decomposition, 简称EMD）是由美国NASA的黄锷博士提出的一种信号分析方法.它依据数据自身的时间尺度特征来进行信号分解, 无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。正是由于这样的特点, EMD 方法在理论上可以应用于任何类型的信号的分解, 因而在处理非平稳及非线性数据上, 具有非常明显的优势。所以, EMD方法一经提出就在不同的工程领域得到了迅速有效的应用, 例如用在海洋、大气、天体观测资料与地震记录分析、机械故障诊断、密频动力系统的阻尼识别以及大型土木工程结构的模态参数识别方面。本工具书主要分以下几个部分：导论、非稳态信号介绍、一维时频信号分解、二维时频信号分解、时频影像信息提取等。
-Time frequency toolbox for use with MATLAB
The Time-Frequency Toolbox has been mainly developed under the auspices
of the French CNRS (Centre National de la Recherche Scientifique). It
results from a research effort conducted within its Groupements de Recherche
”Traitement du Signal et Images” (O. Macchi) and ”Information, Signal et
Images” (J.-M. Chassery). Parts of the Toolbox have also been developed at
Rice University, when one of the authors (PG) was visiting the Department
of Electrical and Computer Engineering, supported by NSF. Supporting institutions
are gratefully acknowledged, as well as M. Guglielmi, M. Najim,
R. Settineri, R.G. Baraniuk, M. Chausse, D. Roche, E. Chassande-Mottin,
O. Michel and P. Abry for their help at different phases of the development.
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Author: 商志远 |
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Description: R-EEMD facilitates
nonuniform and trial-dependent weights obtained by an
optimization procedure during ensemble combination and results
in less decomposition errors when compared with the conventional
ensemble empirical mode decomposition techniques. A theoretic
result is then extended to demonstrate that R-EEMD has an ability
to solve the mode mixing problem frequently encountered in EMD
and improve the decomposition performance with adequate noise
strength when separating a composite two-tone signal. Based on
the proposed R-EEMD framework, a novel clutter rejection filter
for ultrasound color flow imaging is designed
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Author: 唐建 |
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Description: For basic reading and review of HHT algorithm, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
-For basic reading and review of HHT algorithm, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
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Author: golalipour |
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Description: For basic reading and review of HHT algorithm for flickher signal, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
-For basic reading and review of HHT algorithm for flickher signal, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
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Author: golalipour |
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Description: For basic reading and review of HHT algorithm for interruption signal, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
-For basic reading and review of HHT algorithm for interruption signal, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
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Author: golalipour |
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Description: For basic reading and review of HHT algorithm for sag signals, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
-For basic reading and review of HHT algorithm for sag signals, readers are referred to the references [1-4, 6].
For HHT algorithm analysis programs, two resources may be found useful: (1) the Matlab programs which perform most of the HHT algorithm functions available from [7], authored by Zhaohua Wu (2) the R package ‘EMD’ authored by Donghoh Kim and Hee-Seok Oh (published on 29/10/2012). We decide not to use ‘EMD’ package directly for our analysis, because (1) no significance test functionality available (2) no post processing functionality available (3) different stoppage rule in implementation of the EMD process (4) user manual is not very helpful.
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Author: golalipour |
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Description: EEMD\CEEMDAN\EMD的R程序-An R interface for C library libeemd for performing the ensemble
empirical mode decomposition (EEMD), its complete variant (CEEMDAN) or the
regular empirical mode decomposition (EMD).
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Author: 陈寒 |
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