I truely want to understand the functionalities of the highlighted words in the code for better appreciation of the code

phh=zeros(10,10); pmm=zeros(10,10); pmh=zeros(10,10); phm=zeros(10,10); *M=zeros(10,10); H=zeros(10,10)*; source=zeros(10,200,100); *avgT=zeros(10,10); eval= zeros(1, 100); sim = zeros(10, 1)*; *se=zeros(10,1)*; *ce =zeros(10,1)*; *pc= zeros(10,100); c=zeros(10,100); T=zeros(100,100,10); actM=[1 1 1 1 1 0 0 0 0 0]; %cw2= [ 1 0 0 0 0 1 1 1 1 1] ; tq=zeros(10,T); cw3=zeros(1,100)*; q=10; while q <50 d=1; T=zeros(10,100,100); while d <5 %%%%%%%%%%%%%%%%%%%iterating over percentage of malicious packets

phh=zeros(10,10); pmm=zeros(10,10); pmh=zeros(10,10); phm=zeros(10,10); M=zeros(10,10); H=zeros(10,10); iter=1; while iter < 10 %%%%%%look into the following code, it does not run for iterations %%%%%%%%%%%%%%%%generating multiple runs for the given percentage %%%%%%%%%%%%%%%%of malicious packets

             eval=zeros(1,100);
              rp=randperm(100);
              eval(rp(1:q)) = 1;
              cw1=bsc(eval,0.04);
              cw2=zeros(1,100);
              %%%%%%%%%%%formulating  malicious behavior
         %     for i = 1:100
               %if  i < q
               %    if eval(i)==1
               %    cw2(i)=0;

           %        else
            %   cw2(i)=1;

             %      end
             %  else 
           %        cw2(i)=eval(i);

            %     end
         %     end
         cw2=bsc(eval,(q/100));

       source=zeros(100,200,100);
  sim = zeros(10, 1); se=zeros(10,1); ce =zeros(10,1);
  pc= zeros(10,100);
  c=zeros(10,100);
  for i=1:100
      for j=1:10
           source(j,i,:) =eval;% cw1;
        if  rem(i,10)<(d )&& j<((10/2) +1)   &&i>1     %%%%%%%%%%%%%%%%%%%%malicious behavior %%%%%%%%%%%%%%
            source(j,i,:)=cw2;%bsc(eval,q/100);    
        end
      %  if rem(i,10)<d &&j>3&&j<6 %%%%%%%%%%%%%%to have different amounts
      %  of misbehavior
    %        source(j,i,:)=cw3;
     %   end
      for k=1:100
                if (i ==1)
                c(j,k)=1;
                end
                if  (i>1&& source(j,i,k) == source(j,i-1,k))
                 c(j,k) =c(j,k)+1;
                 end
       end

       sim(j)=similar(source(j,i,:),eval);
        se(j)= -sim(j)*log10(sim(j))/log10(100);
         if isnan(se(j))
            se(j)=1;
        end
          pc(j,:)=c(j,:)/i; pc(1,:)=c(1,:)/i;
        sum =0;
        for k=1:100
        sum=(-pc(j,k)*log10(pc(j,k))/log10(100) )+ sum;  % computing the entropy of each source for the whole code word
        end
        ce(j) =sum;
         if isnan(ce(j))
            ce(j)=1; 
         end
       if i <2
      T(d,i,j)=1-se(j); %%%%%%%%d is replaced by d
      else
       T(d,i,j)=(1-(se(j)+ce(j)))*0.5+ 0.5*T(d,i-1,j);
       T(d,i,j)= T(d,i,j)/max(T(d,:,j));
      end
      if (isnan(T(d,i,j)) )
           T(d,i,j)=0;
      end
      if (T(d,i,j)>1)
              T(d,i,j)=1;
      end
        if (T(d,i,j)<0)
              T(d,i,j)=0;
      end

      end
  end

for i = 1: 10 % d*10 to 10 avgT(d,i)=mean(T(d,:,i)); %%%%%%%%%%replacing 'd 'by d if avgT(d,i)<0.75 M(d,i)=M(d,i)+1; if actM(i)==1 pmm (q/10,d)= pmm(q/10,d)+1; else pmh(q/10,d) =pmh(q/10,d)+1; end else H(d,i)=H(d,i)+1; if actM(i)==0 phh(q/10,d)=phh(q/10,d)+1; else phm(q/10,d) =phm(q/10,d)+1; end end end iter =iter+1; end % tp(q/10,d)=pmm(q/10,d)/(pmm(q/10,d)+phm(q/10,d)); tp(q/10,d)=pmm(q/10,d)/(pmm(q/10,d)+phm(q/10,d)); % fp(q/10,d)=pmh(q/10,d)/(phh(q/10,d)+pmh(q/10,d)); fp(q/10,d)=pmh(q/10,d)/(phh(q/10,d)+pmh(q/10,d)); d=d+1;

end

q =q+10; x=1:100; figure(q/10) plot(x,T(1,:,9),'-ob', x,T(1,:,2),'-dr', x, T(2,:,2),'-sg',x,T(3,:,2),'-m*',x,T(5,:,2),'-k^'); legend('Honest', 'Malicious, p =0.1, 10% recommendations are false', 'Malicious,p=0.2, 10% recommendations are false','Malicious,p=0.3, 10% recommendations are false','Malicious,p=0.5, 10% recommendations are false') xlabel('Iteration'); ylabel('RecommendationTrust'); title('Impact of size of recommendation vector');

[Walter Roberson]

Which part should we consider to be highlighted?

Do we get a clue about what the code is intended to do?

Answer 1

[KSSV]

It is called initialization.....when you are going to store the output/result inside the loop, we initialization the respective arrays/Matrices to zeros. This will increase the speed of the code as the memory is already allocated to the result. If there is no initialization code will take long time to run. You can see the difference by commenting those lines and running the code.

Answer 2

[elvin eziama]

for k =1:100

if (i==1)
c(j,k) =1;
if (i>1&& source(j,i,k)== source(j,i-1,k)
c(j,k) = c(j,k)+1

what is the idea behind i>1&& source(j,i,k)== source(j,i-1,k) more especial the i-1

[Walter Roberson]

Run-length encoding of rows. As long as the current location keeps the same value, just increment a counter. When the current location is not the same as the one before, you are just past the end of a run.