Create concurrent bias vectors
S-by-1 bias vector (or an Nl-by-1 cell array of vectors)
and returns an S-by-B matrix of copies of B (or an Nl-by-1 cell array of matrices).
To calculate a layer's net input, the layer's weighted inputs must be combined with its biases. The following expression calculates the net input for a layer with the netsum net input function, two input weights, and a bias:
n = netsum(z1,z2,b)
The above expression works if Z1, Z2, and B are all S-by-1 vectors. However, if the network is being simulated by sim (or adapt or train) in response to Q concurrent vectors, then Z1 and Z2 will be S-by-Q matrices. Before B can be combined with Z1 and Z2, you must make Q copies of it.
n = netsum(z1,z2,concur(b,q))