Sum net input function
Syntax
N = netsum(Z1,Z2,...)
df = netsum('deriv')
Description
netsum is a net input function. Net input functions calculate a layer's net input by combining its weighted inputs and biases.
netsum(Z1,Z2,...,Zn) takes any number of inputs,
and returns N, the element-wise sum of Zi's.
netsum('deriv') returns netsum's derivative function.
Examples
Here netsum combines two sets of weighted input vectors (which we have defined ourselves).
z1 = [1 2 4;3 4 1];
z2 = [-1 2 2; -5 -6 1];
n = netsum(z1,z2)
Here netsum combines the same weighted inputs with a bias vector. Because Z1 and Z2 each contain three concurrent vectors, three concurrent copies of B must be created with concur so that all sizes match up.
b = [0; -1];
n = netsum(z1,z2,concur(b,3))
Network Use
You can create a standard network that uses netsum by calling newp or newlin.
To change a network so a layer uses netsum, set net.layers{i}.netInputFcn to 'netsum'.
In either case, call sim to simulate the network with netsum. See newp or newlin for simulation examples.
See Also
sim, dnetprod, netprod, concur
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