The mean of a signal stored in a matlab row- or column-vector
x can be computed in matlab as

mu = sum(x)/N

or by using the built-in function mean(). If x is a
2D matrix containing N elements, then we need
mu = sum(sum(x))/N
or
mu = mean(mean(x)),
since sum computes a sum along ``dimension 1'' (which is
along columns for matrices), and mean is implemented in terms
of sum. For 3D matrices, mu = mean(mean(mean(x))),
etc. For a higher dimensional matrices x, ``flattening'' it
into a long column-vector x(:) is the more concise form:

N = prod(size(x))
mu = sum(x(:))/N

or

mu = x(:).' * ones(N,1)/N

The above constructs work whether x is a row-vector,
column-vector, or matrix, because x(:) returns a
concatenation of all columns of x into one long
column-vector. Note the use of .' to obtain non-conjugating
vector transposition in the second form. N = prod(size(x)) is
the number of elements of x. If x is a row- or
column-vector, then length(x) gives the number of
elements. For matrices,
length() returns the greater of the number of rows
or columns.^{I.1}