emdoptimset.m

emd经验模态分析 很好的信号分析包 希望大家支持

function options = emdoptimset(varargin)


%   EMDOPTIMSET returns a listing of the fields in the options structure as
%   well as valid parameters and the default parameter. It is written
%   according to the GAOPTIMSET (genetic algoritms toolbox) and OPTIMSET (optimization toolbox) matlab functions.
%   
%   OPTIONS = EMDOPTIMSET(@DI,'PARAM1',VALUE1,'PARAM2',VALUE2,...) creates a structure with the
%   default parameters used in the Doubly-Iterative EMD (see ref. [1]) for all PARAM not specified, and will use the
%   passed arguments VALUE1, VALUE2, etc. for the specified PARAM1, PARAM2,
%   etc.
%
%   OPTIONS = EMDOPTIMSET(@standard,'PARAM1',VALUE1,'PARAM2',VALUE2,....) or just
%   OPTIONS = EMDOPTIMSET('PARAM1',VALUE1,'PARAM2',VALUE2,....) creates a structure with the
%   default parameters used in the standard EMD (see ref. [2]) for all PARAM not specified, and will use the
%   passed arguments VALUE1, VALUE2, etc. for the specified PARAM1, PARAM2, etc.
%
%   OPTIONS = EMDOPTIMSET(OLDOPTS,'PARAM1',VALUE1,'PARAM2',VALUE2,...) will
%   reassign those fields in OLDOPTS specified by PARAM1, PARAM2, ... to 
%   VALUE1, VALUE2, ...
%
%EMDOPTIMSET PARAMETERS
%
% Stopping:    - Several Stopping Criteria.
%              'Nsifts': Each IMF is computed with N siftings.
%              'Nsifts_AND_IMF': Each IMF is computed with at least N
%                   siftings. If after N siftings the IMF criterion is not
%                   fulfilled, i.e. the number of extrema is not equal or +1 to
%                   the number of zerrocrossings, then the siftings continue
%                   until the IMF criterion is become true.
%               'Nsifts_after_IMF': The IMF is computed using N extra
%                   siftings after the IMF criterion become true.
%               'Single_T': Single threshold stopping criterion (see ref.
%               [2]).
%               'Double_T': Double threshold stopping criterion (see ref.
%               [3]).
%
% Nodes:        - The method used for interpolation points selection
%               'Extrema': The maxima and minima used in the conventional
%                   EMD (i.e. as in ref. [2]).
%               'DI_Extrema': The interpolation points are computed
%                   according to the Doubly-iterative EMD principle (see ref.
%                   [1]).
%
% N:            - Positive integer used as 'N' in the Stopping parameter
% 
% T:            - Parameter 'T' in the Stopping parameter 'Single_T'
%                       (positive scalar, i.e. T=0.0001) and the parameter
%                       'Double_T' (three values vector, i.e.
%                       T=[0.05,0.5,0.05] (see ref [3]). 
%
% Order:        - Spline interpolation order (parameter 'q' in ref. [1] page 7). It should take odd integer numbers. (The Matlab Spline toolbox is
%                   needed for interpolation order higher than 3).
%
% in_N:         - Number of internal sifting iterations (parameter 'it' in ref. [1] page 7. It is used with
%                   the DI_Extrema only).
%
% in_Nskip:     - Number of external sifting iterations that the internal
%                   sifting iterations are skipped (parameter 'ex' in ref.
%                   [1] page 7. It is used with the DI_Extrema only).
%
% in_Order:     - Internal sifting Spline interpolation order (parameter
%                   'q' in ref. [1] page 7). It should take odd integer
%                   numbers. (The Matlab Spline toolbox is needed for
%                   interpolation order higher than 3). 
%
% Differentiation: - Method for estimating the derivatives.
%                    'diff_2p': For 2 points estimation.
%                    'diff_5p': For 5 points estimation.
%
% MaxN:         - Maximum Number of sifting iterations independently on
%                   whether the stopping criteria have been fulfilled or not
%
% IMFs:         - Maximum Number of extracted IMFs
%
% Disp:         - 1 for displaying the progress of the decomposition. 0 for
%                   "silent mode".
%
% EXAMPLES:
% options = emdoptimset(@di,'Stopping','Double_T','T',[0.05,0.5,0.05])
% options = emdoptimset(options,'IMFs', 1)
% The Parameters are not case sensitive, and it is not necessary to
% indicated with their full name. i.e.,
% options = emdoptimset('Differentiation','diff_2p','MaxN',100) is equivalent to
% options = emdoptimset('dif','diff_2p','Max',100)
%
% References
% [1] Yannis Kopsinis and Steve McLaughlin, 揑mproved EMD Using
% Doubly-Iterative Sifting and High Order Spline Interpolation,