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atcal.m
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atcal.m
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clc;
close all;
REPETITION = 1;
ITERATIONS = 450; % more and more
lval = [0.5 0.5 0.8 0.5];
noval = [1 1 1 0];
fnmsd = ['msdl2.fig ';'msdl5.fig ';'msdl8.fig ';'msdl5n.fig ' ];
fnmse = ['msel2.fig ';'msel5.fig ';'msel8.fig ';'msel5n.fig ' ];
fnmsdev = ['msdevl2.fig ';'msdevl5.fig ';'msdevl8.fig ';'msdevl5n.fig' ];
lnncolor = ['-r';'-b';'-k';'-g'];
for merged = 1:1
for rep = 1:REPETITION
rep
atcparams();
temp_w = zeros(N,M);
temp_v =zeros(N,M);
int_w = zeros(N,M);
int_v = zeros(2,N);
w_now =zeros(N,M);
vg_now = zeros(N,M);
x_now = zeros(N,M);
v = zeros(M,N);
q = zeros(M,N);
w_true = [100,100]; % is just like that
w_n = zeros(M,N);
psi=zeros(M,N);
phi=zeros(M,N);
n_var = zeros(1,N);
tempxn = x_n;
msd_val = zeros(REPETITION,ITERATIONS);
mse_val = zeros(REPETITION,ITERATIONS);
ms_dis_val = zeros(REPETITION,ITERATIONS);
kappa = 0.01;
lambda = 0.2;
beta = 0.1;
zeta = 0.4;
delta = 0.5;
alpha = 0.05;
no=0; % (0 - No cooperation)
draw=0;
lambda = lval(merged)
no = noval(merged)
merged
for iter = 1:ITERATIONS
%nl = getnmat(x_n, M, N, rmax); % the max no. of nei is also input here
nl = find_nei(x_n',maxneighbors,rmax);
%amatrix = getamatrix(nl)'; ??
amatrix = uniform( nl );
cmatrix = eye(N , N);
for k = 1:N
w_true;
x_n(k,:);
C = kappa .* norm( w_true - x_n(k,:)).^2 * eye(M, M);
n_var(k) = trace(C);
%w_true = w_true';5
q(:,k) = w_true + randn(1,M) * sqrt(n_var(k));
% w_true = w_true';
end
% dif_w = q - w_n;
% diff_v = v_n - vg;
sum_psi=zeros(M,N);
sum_w=zeros(M,N);
sum_phi=zeros(M,N);
sum_v_g=zeros(M,N);
for k=1:N
for l=1:N
sum_psi(:,k)=sum_psi(:,k)+cmatrix(l,k)*(q(:,l)- w_n(:,k));
end
psi(:,k)=w_n(:,k)+mu_w*sum_psi(:,k);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 4 combine %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for l=1:N
sum_w(:,k)= sum_w(:,k)+amatrix(l,k)*psi(:,l);
end
w_n(:,k) = sum_w(:,k);
if (no ~=1)
for l=1:N
sum_phi(:,k)=sum_phi(:,k)+cmatrix(l,k)*(v_n(:,l)- vg(:,k));
end
phi(:,k)=vg(:,k)+mu_v*sum_phi(:,k);
for l=1:N
sum_v_g(:,k)= sum_v_g(:,k)+amatrix(l,k)*phi(:,l);
end
vg(:,k) = sum_v_g(:,k);
else
% No cooperation
for l=1:N
sum_v_g(:,k)= sum_v_g(:,k)+nl(l,k)*v_n(:,l);
end
vg(:,k) = 1/sum(nl(:,k))*sum_v_g(:,k);
end
end
for k = 1:N % loop not required, test and remove
v(:,k) = (lambda * h( w_n(:,k),x_n(k,:)' ,1))...
+ beta * vg(:,k) ...
+ alpha * g(x_n',nl,k,n_var') ...
+ zeta * Delta(x_n',nl,k,2);
x_now(k,:) = x_n(k,:) ;%+ delta * v(:,k)';
end
v_n = v;
x_n = x_now;
msd_val(rep,iter) = (get_msd( N ,w_true, w_n' ));
mse_val(rep,iter) = get_mse( vg,v,N );
ms_dis_val(rep, iter) = get_msdisagree( v, N );
if draw==1
% Targets
plot(w_true(:,1),w_true(:,2),'MarkerSize',8,'MarkerEdgeColor',[1 0 0],'Marker','*');
axis([0 150 0 150])
grid
hold on
text(5,100,0, num2str(iter), 'Color', 'k');
for k=1:N
plot(x_n(k,1),x_n(k,2),'MarkerFaceColor',[1 1 1],'MarkerSize',4,'Marker','o','Color',[0 0 1]);
end
if(iter ==50)
saveas(gcf,'spsh050.fig', 'fig')
end
if(iter == 150)
saveas(gcf,'spsh150.fig', 'fig')
end
if(iter == 300)
saveas(gcf,'spsh300.fig', 'fig')
end
if(iter == 450)
saveas(gcf,'spsh450.fig', 'fig')
end
GF(iter) = getframe;
hold off
end
end
end
if (REPETITION > 1)
msd_mval = mean(msd_val);
mse_mval = mean(mse_val);
ms_dis_mval = mean(ms_dis_val);
else
msd_mval = msd_val;
mse_mval = mse_val;
ms_dis_mval = ms_dis_val;
end
%subplot(3,1,1),
figure(1)
plot(10*log10(msd_mval),lnncolor(merged,:));
title('Transient network MSD for estimating the target location, w(not)')
saveas(gcf,strtrim(fnmsd(merged,:)), 'fig')
%subplot(3,1,2),
figure(2)
plot(10*log10(mse_mval),lnncolor(merged,:));
title('Transient network MSE for estimating the velocity of the center gravity in the far field')
saveas(gcf,strtrim(fnmse(merged,:)), 'fig')
%subplot(3,1,3),
figure(3)
plot(10*log10(ms_dis_mval),lnncolor(merged,:));
title('Transient network mean-square disagreement of the velocities in the far field')
saveas(gcf,strtrim(fnmsdev(merged,:)), 'fig')
%close all;
end