Neural Network Toolbox

netsum

Sum net input function

Syntax

N = netsum(Z1,Z2,...,Zn)

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,

Zi - S x Q matrices,

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

netprod

network