In this tutorial, you will connect groups of neurons to create a system that can multiply two numbers together. You will then modify this network to compute a new function.

Open the partially completed multiplication network

Go to File>Open from file and select partial multiplication.nef.

Connect the network
 The basic components of the network have been constructed for you. Connecting components tells the system to compute the necessary synaptic connection weights to optimally realize the desired function.
 Connect input 1 and input 2 to the inputs for neural ensembles A and B.
 Connect A and B to the two inputs of H.

Connect the product output of H to the input of Z.

Run the network

Rightclick on the background in the Network Viewer and select Interactive plots.
 Click the play button (in the bottomright corner). The grey squares show the firing rates of the neurons.
 The graph displays the decoded output of the network. This should be approximately 40, since the input sliders are currently set to 8 and 5.

Move the sliders up and down to adjust this input. The output will change accordingly.

Change the function being computed

Close the Interactive Plots window.
 Rightclick on the H population and select Add decoded origin. Change the name to
my function
and click Set functions (dimension should be 1). Select userdefined function from the drop down and click set.  Type in a new function. Try
x0*x0+cos(x1)
. You can also use your own function, but the neurons in this example are only optimized for representing values between 100 and 100. Click OK three times.  Disconnect the product projection from H to Z and connect the new origin called my function in its place.
 Rightclick on the Network Viewer and select Interactive plots.
 Adjust the sliders to confirm that the new function is being calculated.
 To compare the behaviour of neurons to the ideal calculation of this function, we can switch simulation modes. Click on the downarrow at the bottom of the interactive plots. Change the mode from default to direct. This will bypass the neurons, producing an exact result.