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1 内容介绍
在本文中，我们提出了一种基于 EquiPartition 原则 (EP) 的信号时间间隔分割方法。 根据 EP，信号被分割成段，在重建中给出相等的误差，选择最合适的模型来描述每个段。 此外，这些片段在内容域中是等效的，因为信号被分割成由相同数量的系数建模的片段。 所提出的方法已成功应用于不同类型的信号，例如：生理、语音、人体运动、金融时间序列。 最后，所提出的方法在误差标准、信号建模和信号维度的变化上非常灵活，从而产生了一种用于信号分割和建模的鲁棒方法。
2 仿真代码
%This code is a simple (not speed optimized) implementation of EP
% based Simultaneous Segmentation and Modelling of Signals, see papers [1-3].
%
close all;
clear all;
S = 7;%number of coefficients
N = 3;%number of segments
%mode = 1; %FFT
%mode = 2; %Polynomial method
%mode = 3; %Wavelet method
mode = 4; %Selection between FFT + Polynomial method + Wavelet (basis selection)
file = 'data\synSignal3Seg-noise_0_025.txt'; %data file
%read data
fid = fopen(file, 'r');
a = fscanf(fid, '%g', [inf]);
a = a';
fclose(fid);
y = a';
figure;
plot(y);
xlabel('samples');
title('signal');
%compute distance matrix
warning('off','all');
[d,meth] = getDistanceFromSignal(y,4,S,1);
%write distance matrix
fileD = sprintf('%s_D.txt',file(1:length(file)-4));
fid = fopen(fileD, 'w');
for i=1:size(d,1),
fprintf(fid,'%f ',d(i,:));
fprintf(fid,'\n');
end
fclose(fid);
%%%EP starts
command = sprintf('ep %s %d data\\ epRes_signal4SegN1-noise',fileD,N);
dos(command);
[Sol1,error1] = getBestSolution(d,'solutionsEQP.txt',N,1);
[Sol2,error2] = getBestSolution(d,'solutions.txt',N,2);
if error1 < error2,
Sol = round(Sol1);
else
Sol = round(Sol2);
end
fclose(fid);
%Sol stores the best EP solution
Segments = Sol;
[y_,error,method] = getReconstruction(y,Segments,mode,S,1);
figure;
hold on;
plot(y,'LineWidth',1.2);
hold on;
plot(y_,'r');
hold on;
%plot(x(points),0,'gs','MarkerFaceColor','g','MarkerSize',6);
for i=2:length(Segments)-1,
plot([Segments(i) Segments(i)],[min(y) max(y)],'-.k');
end
for i=1:length(Segments)-1,
if method(i) == 1,
text(-10+(Segments(i)+Segments(i+1))/2,(min(y)+max(y))/2,'Fourier');
elseif method(i) == 2,
text(-10+(Segments(i)+Segments(i+1))/2,(min(y)+max(y))/2,'Polynomial');
else
text(-10+(Segments(i)+Segments(i+1))/2,(min(y)+max(y))/2,'Wavelets');
end
end
s = sprintf('N = %d, Error = %2.4f, S = %d ',N,error, S);
title(s);
legend('Original','Reconstruction','Segmentation');
xlabel('samples');
3 运行结果
编辑
编辑
编辑
4 参考文献
[1] C. Panagiotakis, K. Athanassopoulos and G. Tziritas, The equipartition of curves,Computational Geometry: Theory and Applications, Vol. 42, No. 6-7, pp. 677-689, 2009.
[2] C. Panagiotakis and G. Tziritas, Signal Segmentation and Modelling based on Equipartition Principle, International Conference on Digital Signal Processing, 2009.
[3] C. Panagiotakis and G. Tziritas, Simultaneous Segmentation and Modelling of Signals based on an Equipartition Principle, 20th International Conference for Pattern Recognition (ICPR), 2010.
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