test.m

matlab中噪声模型

addpath '/home/gari/CODE/MATLAB/MODELS/ECGSYN/LATEST-old/'
[s ipeaks] = ecgsyn(256,300,0);
sampfreq = 256;
t=[1/sampfreq:1/sampfreq:length(s)/sampfreq];
P = find(ipeaks==1);
Q = find(ipeaks==2);
R = find(ipeaks==3);
S = find(ipeaks==4);
T = find(ipeaks==5);

Rreal = maxjiggle(s, R', 5);
df=(R-Rreal');
wrong = find(df>0);
plot(t(R(wrong)),s(R(wrong)),'+r');
title('ECG (blue) with correctly detected peaks in green, incorrect but close in red')

downsample = 1;
N_train=300;
n_lead=1;
downsample=1 
wind=0.5; 

% select the data
[train] =  select_train(s, Rreal, N_train, downsample, downsample, wind);
dataout= energy_normalise(train);

% perform full svd on data
pc = svd(dataout);
totalEig = sum(pc);

% find how many eigenvectors are required to get 
tmpSum = 0;
for (i=1:length(pc))
    tmpSum = tmpSum+pc(i);
    if (tmpSum<=0.95*totalEig)
        eigSig=i;
    end
end

% perform PCA on the matrix of QRS complexes
[U S V] = svds(dataout,eigSig);
recon=(U*U'*dataout);

% plot it all
figure;mesh(dataout);
title('Training vectors')
figure;mesh(recon);
title('Reconstruction of QRS complexes using the first 50 components')