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Title: Matlab runcode Download
 Description: EMD (Empirical Mode Decomposition, generally referred to as EMD Algorithm) is the core algorithm of the Hilbert-Huang Transform (HHT). The Empirical Mode Decomposition (EMD) algorithm is defined by the algorithm process and is not defined by the definite theoretical formula. Therefore, it is very difficult to conduct accurate theoretical analysis on it. We can only rely on a large number of digital simulation tests to continuously evaluate its performance. Conduct in-depth research. The purpose of the EMD algorithm is to decompose a signal with poor performance into a set of better-performing IMMF ntrinsic mode functions, and the IMF must satisfy the following two properties: (1) The number of extreme points (maximum or minimum values) of the signal and the number of zero-crossings are equal or at most one difference;
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FilenameSizeDate
Matlab runcode\Matlab runcode\eemd.m 5276  2009-10-08

Matlab runcode\Matlab runcode\ex02d.m 5152  2009-10-13

Matlab runcode\Matlab runcode\fa.m 7969  2018-03-15

Matlab runcode\Matlab runcode\FSPHSP.m 3794  2009-10-12

Matlab runcode\Matlab runcode\ifndq.m 3502  2009-10-08

Matlab runcode\Matlab runcode\NCU2009V1.txt 7709  2009-10-27

Matlab runcode\Matlab runcode\nnspa.m 8575  2009-10-27

Matlab runcode\Matlab runcode\nnspe.m 8085  2009-10-27

Matlab runcode\Matlab runcode\nspplota.m 7539  2009-10-09

Matlab runcode\Matlab runcode\nspplote.m 7520  2009-10-09

Matlab runcode\Matlab runcode\ratio1.m 664  2009-10-11

Matlab runcode\Matlab runcode\ratioa.m 914  2009-10-11

Matlab runcode\Matlab runcode\significanceIMF.m 2420  2009-10-08

Matlab runcode\Matlab runcode\signiplotIMF.m 2730  2009-10-08

Matlab runcode\Matlab runcode\test.m 1169  2012-10-01

Matlab runcode\Matlab runcode\子系统\blocknormalize.m 4316  2009-10-08

Matlab runcode\Matlab runcode\子系统\confidenceLine.m 5770  2009-10-08

Matlab runcode\Matlab runcode\子系统\dist_value.m 2115  2009-10-08

Matlab runcode\Matlab runcode\子系统\emax.m 853  2009-10-08

Matlab runcode\Matlab runcode\子系统\emin.m 867  2009-10-08

Matlab runcode\Matlab runcode\子系统\endprocess1.m 9997  2009-10-08

Matlab runcode\Matlab runcode\子系统\endprocess1.p 1296  2009-11-25

Matlab runcode\Matlab runcode\子系统\extrema.m 4361  2009-10-08

Matlab runcode\Matlab runcode\子系统\FAacos.m 3356  2009-10-08

Matlab runcode\Matlab runcode\子系统\FAcosfor.m 3013  2009-10-21

Matlab runcode\Matlab runcode\子系统\FAhilbert.m 1528  2009-10-08

Matlab runcode\Matlab runcode\子系统\FAimphilbert.m 1603  2009-10-27

Matlab runcode\Matlab runcode\子系统\FAquadrature.m 7896  2009-10-08

Matlab runcode\Matlab runcode\子系统\FAzc.m 6695  2009-10-08

Matlab runcode\Matlab runcode\子系统\findcriticalpoints.m 3103  2009-10-08

Matlab runcode\Matlab runcode\子系统\findEE.m 6536  2009-10-08

Matlab runcode\Matlab runcode\子系统\findEEfsp.m 11957  2009-10-12

Matlab runcode\Matlab runcode\子系统\fspecial.m 13153  2009-10-11

Matlab runcode\Matlab runcode\子系统\hilbert.m 2207  2009-10-11

Matlab runcode\Matlab runcode\子系统\hilbertnormalize.m 1683  2009-10-08

Matlab runcode\Matlab runcode\子系统\hilbtm.m 18846  2009-10-27

Matlab runcode\Matlab runcode\子系统\linearnormalize.m 3610  2009-10-08

Matlab runcode\Matlab runcode\子系统\local_max.m 2614  2009-10-09

Matlab runcode\Matlab runcode\子系统\LOD-imf.csv 319505  2009-06-08

Matlab runcode\Matlab runcode\子系统\LOD78.csv 29021  2002-09-25

Matlab runcode\Matlab runcode\子系统\medianfilter.m 515  2009-10-08

Matlab runcode\Matlab runcode\子系统\pchipnormalize.m 3651  2009-10-08

Matlab runcode\Matlab runcode\子系统\skiphilbt_m.m 1525  2009-10-08

Matlab runcode\Matlab runcode\子系统\splinenormalize.m 3645  2009-10-08

Matlab runcode\Matlab runcode\子系统\splinenormalizeep.m 4204  2009-10-08

Matlab runcode\Matlab runcode\子系统 0  2018-03-07

Matlab runcode\Matlab runcode 0  2018-03-07

Matlab runcode 0  2018-03-05

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