There are two parts to your question - (a) how to normalise each row of a matrix at once, and (b) how to do it independently for each matrix in a cell array.
(a)
use the dot notation to divide each row by the sum of that row
So for a matrix M,
M = M./sum(M,2); % sum acros the 2nd dimension (column) and do a row-wise division
will normalise each row to sum to 1.
If instead you want to normalise each column, simply:
M = M./sum(M,1);
(b) You can either use a for loop to do the same for each matrix A{jj} of the cell array
for jj=1:N
A{jj} = A{jj}./sum(A{jj},2);
end
A = arrayfun( @(jj) A{jj}./sum(A{jj},2), 1:N , 'UniformOutput', false );
where i use the array fun to loop over 1 to N, setting uniform output to false so my result is also a cell-array. Imagine it like:
output = arrayfun( @jj, func(something), loop over 1 to N, 'UniformOutput', false)
