 技術摘要： |
For multi-dimensional temporal-spatial data, EEMD is applied to time series of each spatial location to obtain IMF-like components of different time scales. All the ith IMF-like components of all the time series of all spatial locations are arranged to obtain ith temporal-spatial multi-dimensional IMF-like component. For two-dimensional spatial data or images, the two-dimensional spatial data or images are consider as a collection of one-dimensional series in first direction along locations in second direction. The same approach to the one used in temporal-spatial data decomposition is used to obtain the resulting two-dimensional IMF-like components. Each of the resulted IMF-like components are taken as the new two-dimensional data for further decomposition, but the data is considered as a collection of one-dimensional series in second-direction along locations in first-direction.
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| 解決的問題或達成的功效： |
extracting intrinsic mode functions of physical data is disclosed, in which the method includes the step of receiving the physical data representative of physical phenomenon
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| 應用領域： |
physical data decomposition
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| 適用產品： |
AI
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| IPC： |
G06K9/0051;
G06F17/14 ;
G06K9/00523;
G06K9/40;
G06K9/527 ;
G06T7/0012;
G06T2207/10088;
G06T2207/10108;
G06T2207/30016 ;
G06T2207/30016
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| Claim 1： |
1. A computer implemented method for extracting intrinsic mode functions of physical data and for analyzing human visible images comprising information from the intrinsic mode functions, the method comprising:
receiving the physical data representative of physical phenomenon;
adding a first kind of white noise series to the physical data;
decomposing the physical data with the added first kind of white noise series into intrinsic mode functions; and
obtaining a mean value of the intrinsic mode functions.
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| 聯繫方式 |
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專利名稱
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