extractevents.m

传感器网络探测声信号通过特征提取进行目标设别分类

function ret = extractevents(runname,nodes)
% Written by Marco F. Duarte 08/13/02
% Extracts event timeseries from whole runs
% ret: Return value (0 indicates normal, -1 indicates error)
% runname: Name of the run to be processed (i.e. 'aav3')
% nodes: vector with node numbers\

%run = 'aav3';
%nodes = [1 2 3 4 5 6 41 42 46 47 48 49 50 51 52 53 54 55 56 58 59 60 61];

for i=nodes,
    eval(['load output\' runname 'label' num2str(i) '.txt']);
    eval(['label = ' runname 'label' num2str(i) ';']);
    eval(['load output\sensit' num2str(i) '-1-' runname '.txt']);
    eval(['acts = sensit' num2str(i) '_1_' runname ';']);
    eval(['load output\sensit' num2str(i) '-2-' runname '.txt']);
    eval(['sets = sensit' num2str(i) '_2_' runname ';']);
    von = find(label == 1);
    if ~isempty(von),
        estart=von(1);
        k=1;
        for j=1:size(von)-1,
            if(von(j) + 1 ~= von(j+1)),
                eend = von(j);
                acevent = acts((((estart-1)*3720)+1):(eend*3720));
                seevent = sets((((estart-1)*3720)+1):(eend*3720));
                eval(['save output\' runname 'event' num2str(k) '_1.txt acevent -ascii;']);
                eval(['save output\' runname 'event' num2str(k) '_2.txt seevent -ascii;']);
                k = k + 1;
                estart = von(j+1);
            end
        end
        eend = von(end);
        acevent = acts((((estart-1)*3720)+1):(eend*3720));
        seevent = sets((((estart-1)*3720)+1):(eend*3720));
        eval(['save output\' runname 'event' num2str(i) '_' num2str(k) '_1.txt acevent -ascii;']);
        eval(['save output\' runname 'event' num2str(i) '_' num2str(k) '_2.txt seevent -ascii;']);
        disp(['Node ' num2str(i) ': ' num2str(k) ' events found (' num2str(von(1)) ':' num2str(von(end)) ').']);
    else
        disp(['Node ' num2str(i) ': no events found.']);
    end
end