for l=10:30

    clearvars countVec tenPercentCountVec noisyVec adjustedCountVec altCountVec

    for k=1:30
        t = linspace(-1*pi,1*pi,1000);
        signal = sin(t); %original signal
        sigma = 0.8; %noise standard deviation
        noisy = signal + sigma*randn(size(signal)); %noisy signal
        noisy10=(noisy.*10)+100;
        noisy10=round(noisy10);
        a=noisy10;

        clearvars  count idx cutOffPlot cutOffPlotTopCutOff cutOffPlotBottomCutOff 
        clearvars TopPeakFinal BottomTroughFinal incrementCountVec realBottomLocPlot  realTopLocPlot
        clearvars cutOff1 cutOff1TopCutOff cutOff1BottomCutOff realBottomLoc1 realTopLoc1
        clearvars closestTopVec closestBottomVec
         

        [m,n]=size(noisy10);
        x=[1:n];
        x=x';
        noisyShift=noisy10';
        f=fit(x,noisyShift,'smoothingspline');
        y=feval(f,x);
        noisyGauss=y;

        [val,loc,width]=findpeaks(noisyGauss);
        [m,n]=size(val);

        %if m>19
            %[altCount]=cemIncrementCountTest(noisy10);
        %elseif m<21
            [finalIncrementCount]=cemIncrementCountCutThree(a);
            %[count]=cemCountHigh(noisy10);
            %end

        %tenPercentCountVec(k)=count;
        %countVec(k)=count;
        altCountVec(k)=ceil(finalIncrementCount);
        if k>2
            if altCountVec(k)<(mean(altCountVec)-2)
                altCountVec(k)=altCountVec(k-1);
            end
        end
        
        noisyVec(k,:)=noisy10;
    end
    
    %countVec(countVec==(l-0.5))=l;
    altCountVec(altCountVec==(l-0.5))=l;
    altCountVec'
    
    countMat((l-9),:)=altCountVec;
    %altCountMat(l-9),:)=altCountVec;
    

end