How can we make this code shorter?

function  APSM
figure
L=200;%Dimension of the unknown vector
N=3500; %Number of Data
theta=randn(L,1);%Unknown parameter

IterNo=100;
MSE1=zeros(N,IterNo);
MSE2=zeros(N,IterNo);
MSE3=zeros(N,IterNo);
MSE4=zeros(N,IterNo);
noisevar=0.3;%For the high noise scenario set this value equal to 0.3
epsilon=sqrt(2)*sqrt(noisevar); %Epsilon parameter used in the APSM
X = randn(L,N);
inputvec = @(n) X(:,n);
noise = randn(N,1)*sqrt(noisevar);
y = zeros(N,1);
y(1:N) = X(:,1:N)'*theta;
y = y + noise;
for It=1:IterNo
    It
    xcorrel = randn(N+L-1,1);
    xcorrel = xcorrel/std(xcorrel);
    X = convmtx(xcorrel,L)';%Generate noise process
    X(:,1:L-1) = [];
    inputvec = @(n) X(:,n);
    noise = randn(N,1)*sqrt(noisevar);%Generate noise process
    y = zeros(N,1);
    y(1:N) = X(:,1:N)'*theta;
    y = y + noise;
    w=zeros(L,1);%Estimate vector
    mu=0.2;
    delta=0.001;
    q=30;% Number of window used for the APA and the APSM.
    for i=1:N
        
        if i>q
            qq=i:-1:i-q+1;
            
            yvec=y(qq);
            Xq=inputvec(qq);
            Xq=Xq';
            
            e=yvec-Xq*w;
            eins=y(i)-w'*inputvec(i);
            w=w+mu*Xq'*inv(delta*eye(q)+Xq*Xq')*e;%APA update
            MSE1(i,It)=eins^2;
        end
    end
    w=zeros(L,1);
    
    for i=1:N
        
        if i>q
            qq=i:-1:i-q+1;
            yvec=y(qq);
            Xq=inputvec(qq);
            Xq=Xq';
            
            sum1=zeros(L,1);
            sum2=0;
            for jj=1:q
                
                p=projection(yvec(jj),Xq(jj,:),w,epsilon);%Compute projection onto hyperslab
                
                sum1=sum1+(1/q)*p;
                sum2=sum2+(1/q)*(((p-w)'*(p-w)));
            end
            
            if sum1==w%Extrapolation Parameter Computation
                Mn=1;
            else
                Mn=sum2/((sum1-w)'*(sum1-w));
            end
            
            eins=y(i)-w'*inputvec(i);
            w=w+Mn*0.5*(sum1-w);%APSM update
            MSE2(i,It)=eins^2;
        end
    end
        
    w=zeros(L,1);%RLS recursion
    delta=0.001;
    Pi=delta*eye(L);
    P=(1/delta)*eye(L);
    for i=1:N
        gamma=1/(1+inputvec(i)'*P*inputvec(i));
        gi=P*inputvec(i)*gamma;
        e=y(i)-w'*inputvec(i);
        w=w+gi*(e);%RLS update
        P=P-(gi*gi')/gamma;
        MSE3(i,It)=e^2;
    end
    
    w=zeros(L,1);%NLMS Recursion
    delta=0.001;
    mu=1.2;
    for i=1:N
        
        e=y(i)-w'*inputvec(i);
        mun=mu/(delta+inputvec(i)'*inputvec(i));
        w=w+mun*e*inputvec(i);%NLMS update
        MSE4(i,It)=e^2;
    end        
end
MSEav1=sum(MSE1')/IterNo;
MSEav2=sum(MSE2')/IterNo;
MSEav3=sum(MSE3')/IterNo;
MSEav4=sum(MSE4')/IterNo;
plot(10*log10(MSEav1),'r');hold on
plot(10*log10(MSEav2),'g');hold on
plot(10*log10(MSEav3),'b');hold on
plot(10*log10(MSEav4),'k')
function [fnew]=projection(y,x,f,epsilon)%Projection onto the hyperslab function
x=x';
inner=f'*x;
if((inner-y<-epsilon))
    fnew=f+((y-inner-epsilon)/(x'*x))*x;
else if (inner-y>epsilon)
        
        fnew=f+((y-inner+epsilon)/(x'*x))*x;
    else
        fnew=f;
    end
end

[darova]

Answer 1

[KALYAN ACHARJYA]

One Suggestion use array or cell array, where it can be, for example-

#Instead of this

MSE1=zeros(N,IterNo);
MSE2=zeros(N,IterNo);
MSE3=zeros(N,IterNo);
MSE4=zeros(N,IterNo);

Use

MSE=cells(1,4)

Instead of this

MSEav1=sum(MSE1')/IterNo;
MSEav2=sum(MSE2')/IterNo;
MSEav3=sum(MSE3')/IterNo;
MSEav4=sum(MSE4')/IterNo;

#DO Array indexing

MSEav(i)=sum(MSE{1}')/IterNo;

See more about vectorization.

[Alice Zurock]

Could you replace in my code your advice, because ı confused how can I type correctly?

[Alice Zurock]

??????