包含源程序代码,可运行,注释全面,很好理解。相关参考文献都配备齐全。
代码片段和文件信息
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 3380817 2018-12-10 16:16 EWT.pdf
文件 1714598 2018-12-31 16:39 gilles2014.pdf
文件 2825 2016-12-01 01:53 EWT1DEWT1D.m
文件 162 2016-12-01 01:53 EWT1DEWT_beta.m
文件 1732 2016-12-01 01:53 EWT1DEWT_InstantaneousComponents.m
文件 1474 2016-12-01 01:53 EWT1DEWT_Meyer_FilterBank.m
文件 920 2016-12-01 01:53 EWT1DEWT_Meyer_Scaling.m
文件 1325 2016-12-01 01:53 EWT1DEWT_Meyer_Wavelet.m
文件 93 2016-12-01 01:53 EWT1DEWT_Single_filter.m
文件 841 2016-12-01 01:53 EWT1DiEWT1D.m
文件 1628 2016-12-01 01:53 EWT1DIFcleaning.m
文件 749 2016-12-01 01:53 EWT1DModes_EWT1D.m
文件 1442 2016-12-01 01:53 EWT2DCurveletAnglesLocalMax.m
文件 2182 2016-12-01 01:53 EWT2DCurveletAnglesLocalMaxMin.m
文件 8620 2016-12-01 01:53 EWT2DCurveletAngular_sector.m
文件 1288 2016-12-01 01:53 EWT2DCurveletCreateAngleGrid.m
文件 8376 2016-12-01 01:53 EWT2DCurveletEWT2D_Curvelet.m
文件 7085 2016-12-01 01:53 EWT2DCurveletEWT2D_Curvelet_FilterBank.m
文件 971 2016-12-01 01:53 EWT2DCurveletEWT2D_Curvelet_Scaling.m
文件 2674 2016-12-01 01:53 EWT2DCurveletEWT_Angles_Detect.m
文件 856 2016-12-01 01:53 EWT2DCurveletiEWT2D_Curvelet.m
文件 3226 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_LittlewoodPaley.m
文件 1529 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_Meyer_FilterBank.m
文件 1011 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_Meyer_Scaling.m
文件 1410 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_Meyer_Wavelet.m
文件 1175 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_UP_Meyer_Wavelet.m
文件 1144 2016-12-01 01:53 EWT2DLittlewood-PaleyiEWT2D_LittlewoodPaley.m
文件 2887 2016-12-01 01:53 EWT2DRidgeletEWT2D_Ridgelet.m
文件 1006 2016-12-01 01:53 EWT2DRidgeletiEWT2D_Ridgelet.m
文件 3970 2016-12-01 01:53 EWT2DTensorEWT2D_Tensor.m
............此处省略99个文件信息
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 3380817 2018-12-10 16:16 EWT.pdf
文件 1714598 2018-12-31 16:39 gilles2014.pdf
文件 2825 2016-12-01 01:53 EWT1DEWT1D.m
文件 162 2016-12-01 01:53 EWT1DEWT_beta.m
文件 1732 2016-12-01 01:53 EWT1DEWT_InstantaneousComponents.m
文件 1474 2016-12-01 01:53 EWT1DEWT_Meyer_FilterBank.m
文件 920 2016-12-01 01:53 EWT1DEWT_Meyer_Scaling.m
文件 1325 2016-12-01 01:53 EWT1DEWT_Meyer_Wavelet.m
文件 93 2016-12-01 01:53 EWT1DEWT_Single_filter.m
文件 841 2016-12-01 01:53 EWT1DiEWT1D.m
文件 1628 2016-12-01 01:53 EWT1DIFcleaning.m
文件 749 2016-12-01 01:53 EWT1DModes_EWT1D.m
文件 1442 2016-12-01 01:53 EWT2DCurveletAnglesLocalMax.m
文件 2182 2016-12-01 01:53 EWT2DCurveletAnglesLocalMaxMin.m
文件 8620 2016-12-01 01:53 EWT2DCurveletAngular_sector.m
文件 1288 2016-12-01 01:53 EWT2DCurveletCreateAngleGrid.m
文件 8376 2016-12-01 01:53 EWT2DCurveletEWT2D_Curvelet.m
文件 7085 2016-12-01 01:53 EWT2DCurveletEWT2D_Curvelet_FilterBank.m
文件 971 2016-12-01 01:53 EWT2DCurveletEWT2D_Curvelet_Scaling.m
文件 2674 2016-12-01 01:53 EWT2DCurveletEWT_Angles_Detect.m
文件 856 2016-12-01 01:53 EWT2DCurveletiEWT2D_Curvelet.m
文件 3226 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_LittlewoodPaley.m
文件 1529 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_Meyer_FilterBank.m
文件 1011 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_Meyer_Scaling.m
文件 1410 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_Meyer_Wavelet.m
文件 1175 2016-12-01 01:53 EWT2DLittlewood-PaleyEWT2D_UP_Meyer_Wavelet.m
文件 1144 2016-12-01 01:53 EWT2DLittlewood-PaleyiEWT2D_LittlewoodPaley.m
文件 2887 2016-12-01 01:53 EWT2DRidgeletEWT2D_Ridgelet.m
文件 1006 2016-12-01 01:53 EWT2DRidgeletiEWT2D_Ridgelet.m
文件 3970 2016-12-01 01:53 EWT2DTensorEWT2D_Tensor.m
............此处省略99个文件信息
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