Introduction - If you have any usage issues, please Google them yourself
Empirical Mode Decomposition (EMD) method (a smooth process) is a new deal with non-stationary data sequence method, the basic idea is: If a raw data sequence X (t) the maximum or minimum number of than the cross-zero (or under the cross-zero) number more than two (or more), then the data is necessary to carry out a smooth sequence of treatment
Packet : 19854833package_emd.rar filelist
package_emd\bugfix.sh
package_emd\revert_bugfix.sh
package_emd\index_emd.m
package_emd\install_emd.m
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package_emd\EMDs\src\cemdc.c
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package_emd\EMDs\src\extr.c
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package_emd\EMDs\src\local_mean.h
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package_emd\EMDs\src\clocal_mean.h
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package_emd\EMDs\src\clocal_mean2.h
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package_emd\EMDs\src\interpolation.h
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package_emd\EMDs\src\emd_complex.h
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package_emd\examples\NSIP2003\triangular_signal.m
package_emd\examples\SPL2007\bivariate_EMD_illustration.m
package_emd\examples\SPL2007\bivariate_EMD_mean_definitions.m
package_emd\examples\SPL2007\bivariate_EMD_principle.m
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package_emd\examples\SPL2007\float_position_record.mat
package_emd\hjd51.txt
package_emd\jl.txt
package_emd\mgs.txt
package_emd\Chinese Loess Plateau Mass Accumulation Rate Data.txt
package_emd\EMDs\src
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package_emd