A 2D lattice
Matlab code
lattice_publish
n = 81;
N = sqrt(n);
ne = 0.5*( 2*4 + (N-2)*3*4 + (N-2)^2*4 );
idx = zeros(2,ne);
for i = 1:N
idx(1,(N-1)*(i-1)+1:(N-1)*i) = N*(i-1)+1:N*(i-1)+(N-1);
idx(2,(N-1)*(i-1)+1:(N-1)*i) = N*(i-1)+2:N*(i-1)+N;
end
for i = 1:N
idx(1,ne/2+ ((N-1)*(i-1)+1:(N-1)*i) ) = i:N:(i+(N-2)*N);
idx(2,ne/2+ ((N-1)*(i-1)+1:(N-1)*i) ) = (i:N:(i+(N-2)*N))+N;
end
Eg = incmat(idx);
L = Eg*Eg';
kappa = diag(L);
kval = 1:1:40;
Jlow = zeros(size(kval));
Jup = zeros(size(kval));
LSgreed = zeros(n,length(kval));
for i = 1:length(kval)
Nl = kval(i);
flag = 1;
[Jlow(i),Jup(i),LSgreed(:,i)] = leaders(L,Nl,kappa,flag);
end
Computational results
Performance bounds
Bounds on the global optimal value of the noise-corrupted leader selection problem
for the 2D lattice example.
Selection of leaders
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Selection of noise-corrupted leaders () obtained using
greedy algorithm (i.e., one-leader-at-a-time algorithm followed by the swap procedure)
for the 2D lattice example.
For , the center node provides the optimal
selection of a single leader. As increases, nodes away from the center
node are selected; for example, for , nodes , are
selected and for , nodes , , are selected.
Selection of nodes farther away from the center becomes more significant for
and .
The selection of leaders exhibits symmetry with respect to the center
of the lattice. For example, in Fig. (b), the leaders at , denoted by
() provide the same objective function as leaders denoted by (). Similarly,
in Fig. (c), the four selections of three leaders denoted by (), (),
(), and () all provide the same performance .
Also note that when is large, almost uniform spacing between leaders is
observed; see Fig. (f). This is in contrast to the random network example where boundary nodes were selected when the number
of leaders is large.
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