biorthogole 小波
语法: BiorthogonalWavelets(imageStr,iter,cf) ;(*)
%Biorthogonalwavelets(imagestr,iter,cf,"cdf",l,lt);
%Biorthogonalwavelets(imagestr,iter,cf,"spline",n,nt);
%Biorthogonalwavelets(imagestr,iter,cf,h,ht,g,gt,inds_h,inds_ht,inds_g,inds_gt);
%[IM IMt IMtc IMhat] = BiorthogonalWavelets(imageStr,iter,cf);
%[IM IMt IMtc IMhat] = BiorthogonalWavelets(imageStr,iter,cf,"CDF",l,lt);
%[IM IMt IMtc IMhat] = BiorthogonalWavelets(imageStr,iter,cf,"spline",N,Nt);
%[IM IMt IMtc IMhat] = BiorthogonalWavelets(imageStr,iter,cf,h,ht,g,gt,inds_h,inds_ht,inds_g,inds_gt);
%
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- 2023-02-04 15:55:04下载
- 积分:1
条件随机场链式CRF
机器学习算法代码,可以用于分词,图像识别,行为识别等
原版本只可以在32位xp下运行,经本人修改,适用于各种版本matlab windows
clear all
useMex = 0; % Set this to 1 to use mex files to speed things up
%% Generate Synthetic Data
% Notes:
% - X is categorical, each element X(i,j) contains the value of feature j for word i,
% a value of "0" means ignore the feature for this training example
% - y is cateogircal, each element y(i) contains the label for word i
% a value of "0" indicates the position between sentences
[X,y] = crfChain_genSynthetic;
nWords = size(X,1);
nStates = max(y);
nFeatures = max(X);
%% Initialize parameters and data structures
[w,v_start,v_end,v] = crfChain_initWeights(nFeatures,nStates,"randn");%初始化参数为正太分布,w状态-特征,v状态-状态
featureStart = cumsum([1 nFeatu
- 2022-04-19 10:41:14下载
- 积分:1