Drawing a non-bipartite graph in MATLAB

Drawing a non-bipartite graph in MATLAB - matlab

I am looking to draw a graph in MATLAB. My graph is non-bipartite and the matrix for the graph is:
A=[0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 %1
1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 %2
0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 %3
0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 %4
0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 %5
1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 %6
0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 %7
0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 %8
0 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 %9
0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 %10
0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 %11
1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 %12
0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 %13
0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 %14
1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 %15
0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0]; %16
When this graph is drawn in MATLAB, the node numbered 16 is to the left of the graph but this should be in the centre.
Is there a way to set up my matrix so that the node 16 is in the centre making the graph non-bipartite?

Not sure how you're plotting the graph, but on my Win10-x64 R2017b I get that 16 is the closest point to the center:
function q47392076
A=[0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 %1
1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 %2
0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 %3
0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 %4
0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 %5
1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 %6
0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 %7
0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 %8
0 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 %9
0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 %10
0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 %11
1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 %12
0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 %13
0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 %14
1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 %15
0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0]; %16
G = graph(A);
figure(); plot(G);
end

Related

Simulate obstacles in logical matrix

I'm writing an optimal path planning algorithm for one of my projects, and am a bit stuck on how to generate the map. In order to test my algorithm, I want to generate random maps that the object will pass through with obstacles in the way. To generate the maps I am making a logical array with "1" for wall or obstacle and "0" when there is nothing in the way. I am having some issues placing the obstacles however.
For now, this is what I've written in MATLAB (though I think the core idea can be solved in any language):
% lenx = length in x-direction of map [m]
% leny = length in y-direction of map [m]
% numObs = number of obstacles
% obsLoc = 2D array with the central location(s) of the obstacle(s)
% [x1, y1; x2 y2; ...]
% obsSize = size of the obstacles (all same size) [m]
% assume the obstacles are square.
% res = resolution of the map [cell/m]
%
% Outputs:
% map = 2D logical array which translates into a map
%
%---------------------------------------------------------
function map = createMap(lenx, leny, numObs, obsLoc, obsSize, res)
%Making map of the given size
map = zeros(leny*res, lenx*res);
%Adding walls
map(:,1) = 1;
map(:, lenx*res) = 1;
map(1,:) = 1;
map(leny*res, :) = 1;
%Recalculating obstacle size for this grid
obsSize = obsSize - 1;
%Adding obstacles
for i = 1:1:numObs
map(obsLoc(i,1)*res-obsSize*res:obsLoc(i,1)*res+obsSize*res,...
obsLoc(i,2)*res-obsSize*res:obsLoc(i,2)*res+obsSize*res) = 1;
end
end
The obsSize parameter is representing the dimension of one of the sides of the square obstacle. Here is a sample solution I ran:
>> createMap(10,10,1,[5,5],1,1)
ans =
1 1 1 1 1 1 1 1 1 1
1 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 1
1 0 0 0 1 0 0 0 0 1
1 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 1
1 1 1 1 1 1 1 1 1 1
Looks good! But the issue begins for obstacle sizes and resolutions that are not 1 or 2...
>> createMap(10,10,1,[5,5],0.5,2)
ans =
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
>> createMap(10,10,1,[5,5],3,2)
ans =
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
For the first one, we would expect there to be a 1 somewhere close to the middle, but it's nowhere to be found. In the second one, we'd expect to find 6 ones in each direction (3m * 3cell/m = 6 cell), but we are getting 8 (It's also possible that this is not what my code is calculating, but this is what I'm hoping it does. Neither case is working, and I think it has to do with this line:
Recalculating obstacle size for this grid
obsSize = obsSize - 1;
I'm pretty sure I do have to recalculate the object size so it fits to the grid, but how can I do this for any grid and obstacle? Is there a way to scale that "-1" such that it acts according to the size of the grid/obstacle?
Let me know what you come up with, and if there's any other glaring issues in my code?
Thanks!

MxN matrix with ones and zeros following a specific rule

I want to create a MxN matrix as shown below:
[1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0;
0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0;
0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0;
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0;
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1]
I have window size, let's say, 5 and it moves 3 in every row. Is it possible to create such a matrix without using for loops? Or is there any optimum way to do it?

This is a one line solution:
reshape([reshape([ones(5,6);zeros(21,6)], 1,[]), ones(1,5)],[],7).'
note:
The desired matrix can be seen as concatenation of a [6, 5+21] matrix:
1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
and a [1 ,5] matrix:
1 1 1 1 1
that reshaped to a [7 , 23] matrix.
Other solution using repelem + bsxfun + accumarray:
r = repelem (1:7,5);
c= bsxfun(#plus, ((1:5)-3).',3*(1:7));
out = accumarray([r(:) c(:)] ,1)
Indices of rows and columns of 1 s can be generated and accumarray can be used to create the desired matrix.

Plotting a tour from an MST

I am new to matlab coding and I would like to know how to plot a tour visiting all points in a minimum spanning tree (yes, TSP/TSM). I was given a set of points a matrix of 20x2 and I was able to find out the MST of these points and I need help figuring out how to plan a tour of these points of minimum possible distance?
my adj matrix for the MST is,
X_st =
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0
1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1
0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0
1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0
0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0
0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Obtained from kruskal algorithm to plot a MST of a complete graph.
My, neighbouring weighted matrix obtained from kruskal function is,
1 3
7 17
5 20
6 14
1 17
6 20
16 19
2 14
7 11
6 18
12 19
14 16
10 19
8 11
2 8
3 15
9 18
4 19
13 15
Any guidance would be much appreciated.

once you have extracted the points for the MST using krushkals algorithm u need to use f=figure then for each (x,y) point it has to be like f = f + plot(x1,y1,x2,y2,[options]) plot and the plot code should be surrounded by hold on hold off please let me know if the answer was helpful the complete snippet will be like
f = figure;
hold on
f = f + plot(x1,y1,x2,y2) //put this in a loop for all points
hold off

Matrix Exponentiation in Galois Field 2

I am confusing about exponentiation of matrix in Galois Field 2. Assume that I have a matrix that is represented in Galois Field 2 (GF2). I want to take exponentiation of 30. That is,
A^30
In the matlab we have two way to do it.
First, We perform A power 30 and take mod of 2 (Note that A is a double matrix)
A1=mod(A^30,2)
Second way, we convert A to galois matrix and take exponentiation
A=gf(A,2)
A2=A^30
Actually, two way must same result. However, when I check A1 and A2. They have a different result. What is happen in here? Thanks
Let see my A matrix
A =
1 1 0 1 1 1 0 1 0 0 0 1 0 1 0
0 0 0 1 0 1 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 1 0 1 0 0 0 1
1 0 1 1 0 0 0 0 0 0 1 1 1 0 0
1 0 1 0 0 0 0 1 0 0 0 0 0 0 0
0 1 0 1 1 1 1 1 0 1 1 1 1 0 1
0 0 0 1 0 0 0 1 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
1 0 0 1 0 1 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 0 0 1 1
1 0 1 0 0 0 0 0 0 0 1 0 0 0 1
0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
1 0 1 1 1 1 1 1 1 0 1 1 1 0 1
0 1 0 0 0 1 0 0 0 1 0 0 0 1 0
1 0 0 1 0 1 0 0 0 1 0 0 0 1 1
Method1:
A1=
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Method 2
A2 =
1 1 0 1 1 1 0 1 0 0 0 1 0 1 0
0 0 0 1 0 1 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 1 0 1 0 0 0 1
1 0 1 1 0 0 0 0 0 0 1 1 1 0 0
1 0 1 0 0 0 0 1 0 0 0 0 0 0 0
0 1 0 1 1 1 1 1 0 1 1 1 1 0 1
0 0 0 1 0 0 0 1 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
1 0 0 1 0 1 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 0 0 1 1
1 0 1 0 0 0 0 0 0 0 1 0 0 0 1
0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
1 0 1 1 1 1 1 1 1 0 1 1 1 0 1
0 1 0 0 0 1 0 0 0 1 0 0 0 1 0
1 0 0 1 0 1 0 0 0 1 0 0 0 1 1

detect digits with hopfield Neural network in matlab

I want to detect digist with hopfield.for any digit let 96 cell ( 8*12).
my data are
zero=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
one=[0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 ];
two=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
three=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
four=[0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 ];
five=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
six=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
seven=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ];
eight=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
nine=[0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 ];
target =[zero;one;two;three;four;five;six;seven;eight;nine];
and create a hopfield with newhop
net = newhop(target);
[Y,Pf,Af] = sim(net,10,[],target);
I conclusion this from matlab website
but really I don't know How I achive this
my project is detect digits by hopfield network
appreciate any orgency help

Try:
target =[zero;one;two;three;four;five;six;seven;eight;nine]';
Then, for a test:
test={three'};
[Y,Pf,Af] = sim(net,{1 5},{},test);
Y{1}
You'll notice that Y{1}-three' is very close to zero, which means that your network does its job. Now, in order to recognize the digit you enter, you need to subtract Y{1} from the matrix of digits and check the row the elements of which are closest to zero. This will indicate you the digit you entered.

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Drawing a non-bipartite graph in MATLAB - matlab

Related

Simulate obstacles in logical matrix

MxN matrix with ones and zeros following a specific rule

Plotting a tour from an MST

Matrix Exponentiation in Galois Field 2

detect digits with hopfield Neural network in matlab

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