could anyone help me how to have the same values for all the three clusters with respect to the code shown below.

code:

clear all;
clc;
PPP=[2.6917    0.3600;
    1.6045    0.5565;
   -0.8608    0.8706;
    1.3589    0.4763]
particles =1; 
iterations = 3;
dimensions=2;
swarm_fitness(1:particles)=-Inf;
clusters=zeros(1,particles);
swarm_pos = cell(1,particles);
swarm_vel = cell(1,particles);
swarm_best = cell(1,particles);
 for particle=1:particles
     PARTICLE=particle;
     clusters(particle)= 3;
     swarm_pos{particle} [ 0.9625    0.9028;
                           0.9824    0.1940;
                           0.7983    0.3804]
     initial_clusters=size(swarm_pos{particle},1);
end
for T=1:iterations 
    for  particle=1:particles
     [mm,nn] = size(swarm_pos{particle});
           distance=[];
             for user=1:4
                    for cluster=1:mm
           distance(user,cluster)=norm(swarm_pos{particle}(cluster,:)-PPP(user,:));
                    end
            end
     distances{particle}=distance;
    end
c=zeros(4,particles);
   for particle=1:particles
    [value, index] = max(distances{particle},[],2);
    c(:,particle) = index;
   end
  average_fitness = zeros(particles,1);
 for particle=1:particles
      [mm,nn] = size(swarm_pos{particle});
        for cluster = 1 : mm
            if any(c(:,particle) == cluster)
             CC_CC=c(:,particle)==cluster;cluster;particle;
             CCC_CCC=distances{particle};
             cc1=CCC_CCC(:,cluster);
             ccc1=CC_CC';
             cc2=sum(ccc1(:)==1);
             cc3= ccc1*cc1;
             local_fitness=cc3/cc2;%minimum value/average
             average_fitness(particle,1) = average_fitness(particle,1) + local_fitness;% adding the fitness of cluster together
            end
        end
        average_fitness(particle,1) = average_fitness(particle,1) / mm;
        if (average_fitness(particle,1) > swarm_fitness(particle));
            ss=(average_fitness(particle,1) > swarm_fitness(particle));
            swarm_fitness(particle) = average_fitness(particle,1);
            swarm_best(:,particle) = swarm_pos(:,particle); %LOCAL BEST FITNESS
        end
 end
r1=0.2
w=0.8;
c1=2.7455;
        for particle=1:particles 
        P2=particle;
        C2C2=swarm_pos{particle}
        cognitive =c1*r1*(swarm_best{particle}-swarm_pos{particle});
        end
end

When i run the code it executes and gives me the result where

C2C2 =[ 0.9625    0.9028;
        0.9824    0.1940;
       0.7983    0.3804]

But i want to have C2C2 such that all the three rows should contain the same values in the following manner

C2C2 =[ 0.9625    0.9028;
        0.9625   0.9028;
       0.9625   0.9028]
  

or

C2C2=[0.9824    0.1940;
      0.9824    0.1940;
      0.9824    0.1940]

or

C2C2=[0.7983   0.3804;
      0.7983   0.3804;
      0.7983   0.3804]

Could anyone please help me on this.

[Adam]

You haven't given any description of what you are trying to do. From the numbers you give your example seems to just boil down to

C2C2=swarm_pos{particle}

and given what you want then I guess

C2C2 = repmat( swarm_pos{particle}(1,:), [3 1] );

would work, which completely ignores almost every line of the code you included!