# How to find the Laplacian Matrix with Network, please

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AMA on 11 Jun 2021
Hi Dear
If we difine L_{ij} of the graph Laplacian are defined by L_{ij} = A_{ij}- k_i delta_{ij}, where A is the adjacency matrix, k_{i} is the degree of node i, delta_{ij} is the Kronecker delta, and where we do not sum over repeated indices.
N=200;L=100; coverage_range=20;
% random coordination
distinct_BOUND = 5;
P = zeros(N,2);
% rand(1,2)<0.05;
Q = rand(1,2)*L;
P(1,:) = Q;
for j = 2:N
u = true;
m = false;
while u || m
Q = rand(1,2)*L ;
% u is true if new added node is too far to all node
u = true;
for i = 1:j-1
if pdist([Q;P(i,:)],'euclidean') < coverage_range
%D = pdist(X) returns the Euclidean distance between pairs of observations in X.
u = false;
end
end
% m is true if new added node is too near to one node
m = false;
for i = 1:j-1
if pdist([Q;P(i,:)],'euclidean') < distinct_BOUND
m = true;
end
end
end
P(j,:) = Q;
end
figure;
OP=gscatter(P(:,1),P(:,2));
r = sprintf('N-%d,L-%d, cr-%d nodes', N, L, coverage_range);
could you help me to find Laplacian, I use Laplacian() but it didn't work, please