EWT最新经验小波变换工具箱

经验小波变换工具箱在使用上感觉效果比EMD好些，还在学习中，希望对大家有用 The purpose of this document is to provide useful information on how is or- ganized and how use the Empirical Wavelet Transform Toolbox (EWTT), not to explain what are the principles of the Empirical Wavelet Transform. In this document, we assume that the reader knows what is the EWT and how it works. If it is not the case, I advise you to read the papers

function [ewtmfbboundaries]=EWT1D（fparams）

% =========================================================================
% function [ewtmfbboundaries]=EWT1D（fparams）
% 
% Perform the Empirical Wavelet Transform of f over Nscale scales. See 
% also the documentation of EWT_Boundaries_Detect for more details about
% the available methods and their parameters.
%
% Inputs:
%   -f: the input signal
%   -params: structure containing the following parameters:
%       -params.log: 0 or 1 to indicate if we want to work with
%                    the log spectrum
%       -params.preproc: ‘none‘‘plaw‘‘poly‘‘morpho‘tophat‘
%       -params.method: ‘locmax‘‘locmaxmin‘‘locmaxminf‘‘adaptive‘
%                       ‘adaptivereg‘‘scalespace‘
%       -params.reg: ‘none‘‘gaussian‘‘average‘‘closing‘
%       -params.lengthFilter: width of the above filters
%       -params.sigmaFilter: standard deviation of the above Gaussian
%                            filter
%       -params.N: maximum number of supports
%       -params.degree: degree of the polynomial （needed for the
%                       polynomial approximation preprocessing）
%       -params.completion: 0 or 1 to indicate if we try to complete
%                           or not the number of modes if the detection
%                           find a lower number of mode than params.N
%       -params.InitBounds: vector of initial bounds （in index domain）
%                           needed for the adaptive and adaptivereg methods
%				-params.typeDetect: （for scalespace method only） ‘otsu‘
%                           ‘halfnormal‘‘empiricallaw‘‘mean‘‘kmeans‘
%
% Outputs:
%   -ewt: cell containing first the low frequency component and
%         then the successives frequency subbands
%   -mfb: cell containing the filter bank （in the Fourier domain）
%   -boundaries: vector containing the set of boundaries corresponding
%                to the Fourier line segmentation （normalized between
%                0 and Pi）
%
% Author: Jerome Gilles
% Institution: UCLA - Department of Mathematics
% Year: 2013
% Version: 2.0
% =========================================================================

%% Boundary detection
% We compute the Fourier transform of f
ff=fft（f）;
% We extract the boundaries of Fourier segments
boundaries = EWT_Boundaries_Detect（abs（ff（1:round（length（ff）/2）））params）;
boundaries = boundaries*pi/round（length（ff）/2）;

%% Filtering
% We extend the signal by miroring to deal with the boundaries
l=round（length（f）/2）;
f=[f（l-1:-1:1）;f;f（end:-1:end-l+1）];
ff=fft（f）;

% We build the corresponding filter bank
mfb=EWT_Meyer_FilterBank（boundarieslength（ff））;

% We filter the signal to extract each subband
ewt=cell（length（mfb）1）;
for k=1:length（mfb）
    ewt{k}=real（ifft（conj（mfb{k}）.*ff））;
    ewt{k}=ewt{k}（l:end-l）;
end

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     文件        2825  2016-12-01 01:53  EWT\1D\EWT1D.m
     文件        1732  2016-12-01 01:53  EWT\1D\EWT_InstantaneousComponents.m
     文件        1474  2016-12-01 01:53  EWT\1D\EWT_Meyer_FilterBank.m
     文件         920  2016-12-01 01:53  EWT\1D\EWT_Meyer_Scaling.m
     文件        1325  2016-12-01 01:53  EWT\1D\EWT_Meyer_Wavelet.m
     文件          93  2016-12-01 01:53  EWT\1D\EWT_Single_filter.m
     文件         162  2016-12-01 01:53  EWT\1D\EWT_beta.m
     文件        1628  2016-12-01 01:53  EWT\1D\IFcleaning.m
     文件         749  2016-12-01 01:53  EWT\1D\Modes_EWT1D.m
     文件         841  2016-12-01 01:53  EWT\1D\iEWT1D.m
     文件        1442  2016-12-01 01:53  EWT\2D\Curvelet\AnglesLocalMax.m
     文件        2182  2016-12-01 01:53  EWT\2D\Curvelet\AnglesLocalMaxMin.m
     文件        8620  2016-12-01 01:53  EWT\2D\Curvelet\Angular_sector.m
     文件        1288  2016-12-01 01:53  EWT\2D\Curvelet\CreateAngleGrid.m
     文件        8376  2016-12-01 01:53  EWT\2D\Curvelet\EWT2D_Curvelet.m
     文件        7085  2016-12-01 01:53  EWT\2D\Curvelet\EWT2D_Curvelet_FilterBank.m
     文件         971  2016-12-01 01:53  EWT\2D\Curvelet\EWT2D_Curvelet_Scaling.m
     文件        2674  2016-12-01 01:53  EWT\2D\Curvelet\EWT_Angles_Detect.m
     文件         856  2016-12-01 01:53  EWT\2D\Curvelet\iEWT2D_Curvelet.m
     文件        3226  2016-12-01 01:53  EWT\2D\Littlewood-Paley\EWT2D_LittlewoodPaley.m
     文件        1529  2016-12-01 01:53  EWT\2D\Littlewood-Paley\EWT2D_Meyer_FilterBank.m
     文件        1011  2016-12-01 01:53  EWT\2D\Littlewood-Paley\EWT2D_Meyer_Scaling.m
     文件        1410  2016-12-01 01:53  EWT\2D\Littlewood-Paley\EWT2D_Meyer_Wavelet.m
     文件        1175  2016-12-01 01:53  EWT\2D\Littlewood-Paley\EWT2D_UP_Meyer_Wavelet.m
     文件        1144  2016-12-01 01:53  EWT\2D\Littlewood-Paley\iEWT2D_LittlewoodPaley.m
     文件        2887  2016-12-01 01:53  EWT\2D\Ridgelet\EWT2D_Ridgelet.m
     文件        1006  2016-12-01 01:53  EWT\2D\Ridgelet\iEWT2D_Ridgelet.m
     文件        3970  2016-12-01 01:53  EWT\2D\Tensor\EWT2D_Tensor.m
     文件        1591  2016-12-01 01:53  EWT\2D\Tensor\iEWT2D_Tensor.m
     文件        1629  2016-12-01 01:53  EWT\Boundaries\Adaptive_Bounds_Adapt.m
     文件         835  2016-12-01 01:53  EWT\Boundaries\EWT_Boundaries_Completion.m
............此处省略67个文件信息