如何将不同长度的向量插入矩阵？例如，我有一个随机定位的节点= 10;之后我发现谁是这个节点的邻居，例如节点：i = 2个邻居是节点：j = 5和6，所以包含这个值的向量是neighb_i = [neighb_i j];但也许我必须添加一些零来填充向量，直到矩阵的长度（在这种情况下节点是10，所以矩阵将是10x10）但我想保留矩阵中所有节点的邻居的所有值，因为当我在下一次交互后使用向量时，这个值正在替换自己，所以在下一次迭代时，当i = 3时，我没有关于何时i = 2的信息。我怎样才能将它存储在矩阵中，长度节点x节点？
close all
clear all
clc
x = 2000; %m
y = 2000; %m
nodes = 8;
%% Random location and direction, calculating the distance;
loc_x = x*rand(1,nodes)
loc_y = y*rand(1,nodes)
loc = [loc_x' loc_y']
dist(loc_x);
dist(loc_y);
distance = sqrt(dist(loc_x).^2 + dist(loc_y).^2) % = dist(loc')
distance(1:nodes+1:nodes^2) = inf; % replace zero diagonal with infinity
%% Power:
noise_power_dBm = -90; %dBm
noise_power_w = 10^((noise_power_dBm - 30)/10); % W
% The channel is based on a path-loss model in which is distance between nodes i and j
% and 3 - is attenuation exponent considerd as 3 ( 1:6 )
channel_gain = (1)./(distance).^3; %dB
channel_gain(1:nodes+1:nodes^2) = inf; % replace zero diagonal with infinity
min_SNR_dB = 10; %dB, minimum required SNR at the receiving nodes
min_SNR = 10^(min_SNR_dB/10);
p_max_dBm = 10; % dBm
p_max_w = 10^((p_max_dBm - 30)/10); % W
p_uni = (min_SNR*noise_power_w)./(channel_gain); % unicast power between two nodes
p_uni(1:nodes+1:nodes^2) = inf; % replace zero diagonal with infinity
plot(loc_x,loc_y,'r*');
change = 1;
cost = inf(1,nodes) % at the beginning cost of all nodes are infinity
cost(1) = 0; % except the cost of node 1 = 0 ( source node )
while change == 1 % change is when a child chooses parent node and change its parent node; if its a =1 its go again in for loops
change = 0; % when i am coming inside while loop I change the change parameter to 0 and if some changes occurse
for i = 2:nodes %i - child node first i = 2, then j is 1,2,3...8 it checks all the nodes starts from 1 because source node can be a neighbour of other node
neighb_i = [];
for j = 1:nodes % j - parent node
if p_uni(i,j) < p_max_w
neighb_i = [neighb_i j]; %Found who are the neighbours ; to use a matrix not a vector ????????
end
% calculate the cost for every nodes First Dijkstra, later MC
% and choose the parent node for every node ; if we have some changes
% ---> change = 1
for k = [neighb_i j] % neighb_i
% cost(i,k) = 1:nodes;
end
end
keyboard
end
% At the end of this while - I have to know what is the parent node for
% every node and when I come out I can draw a graph.
end
%%
gplot(nodes,loc)
%plot(source,'b*');
plot(loc_x,loc_y,'rO');
axis([x y x y]);
hold on;
grid on;
grid on, xlabel('x'), ylabel('y');
title('Random nodes');