block descriptions of networks so you can simulate them using Simulink® software.
The second argument to
the sample time, which is normally chosen to be some positive real
If a network has no delays associated with its input weights
or layer weights, this value can be set to -1. A value of -1 causes
generate a network with continuous sampling.
Here is a simple problem defining a set of inputs
p = [1 2 3 4 5]; t = [1 3 5 7 9];
The code below designs a linear layer to solve this problem.
net = newlind(p,t)
You can test the network on your original inputs with
y = sim(net,p)
The results show the network has solved the problem.
y = 1.0000 3.0000 5.0000 7.0000 9.0000
gensim as follows to generate a Simulink version
of the network.
The second argument is -1, so the resulting network block samples continuously.
The call to
gensim opens the following Simulink Editor,
showing a system consisting of the linear network connected to a sample
input and a scope.
To test the network, double-click the input Constant
on the left.
The input block is actually a standard Constant block. Change
the constant value from the initial randomly generated value to
and then click OK.
Select the menu option Simulation > Run. Simulink takes a moment to simulate the system.
When the simulation is complete, double-click the output
on the right to see the following display of the network’s
Note that the output is 3, which is the correct output for an input of 2.
Here are a couple exercises you can try.
Replace the constant input block with a signal generator from the standard Simulink Sources blockset. Simulate the system and view the network’s response.
Recreate the network, but with a discrete sample time of 0.5, instead of continuous sampling.
Again, replace the constant input with a signal generator. Simulate the system and view the network’s response.
For information on simulating and deploying neural networks with MATLAB® functions, see Deploy Trained Neural Network Functions.