h <code>update: true</code> then
the weights will be updated after the last propagation, but the deltaweights of
the first 3 propagation will be included too.</p>
<pre>
var myNetwork = new Network(1,1);

// This trains the network to function as a NOT gate
for(var i = 0; i < 1000; i++){
  network.activate([0]);  
  network.propagate(0.2, 0, true, [1]);

  network.activate([1]);
  network.propagate(0.3, 0, true, [0]);
}
</pre>

<p>The above example teaches the network to output <code>[1]</code> when input <c