Mimic
Mimic is a simple perceptron. It's purpose is to learn to fire a single
output neuron when the corresponding input neuron if fired. The network
may be trained automatically or manually.
Neurons are circles in various shades of pink. The brighter the shade,
the more active the neuron is. Neurons which are not firing at all are
black. Connections are represented by rectangles running between
neurons. Positive connections are blue; negative connections are red.
The stronger a connection, the thicker the rectangle. The Mimic network
has four input neurons on the left, two hidden layer neurons in the
middle, and four output neurons on the right.
The patterns that the network is to learn are shown in the four small
boxes in the upper right of the applet. On the left of each box is an
input pattern, on the right the output pattern which the network is to
learn. Clicking on one of the boxes with the mouse copies that boxes
input pattern into the network and propogates it through to the output.
If the network is not trained, the output will be wrong and further
training will be needed.
To train the network manually, all the connection strengths must be
adjusted by hand. To increase the strength of a connection, left-click
on it. To decrease the strength, right-click on it. (If you only have
one mouse button, click to increase and shift-click to decrease.)
NOTE: Increasing the strength of a negative connection makes it less
negative so the connection will appear smaller. Decreasing the
strength makes it more negative so the connetion will appear larger.
If you decrease the strength of a positive connection far enough, it
will become negative. Increasing the strength of a negative connection
sufficiently will make it positive
Sometimes clicking on a connection makes too small a change to see the
difference, clicking several times in a row should make the change
visible. Also, there is a mimimum and a maximum width to the
connections. Beyond those boundaries, changes in strength can not be
seen but may still occur.
Clicking the train button cycles through the four input patterns and
trains the network to produce the correct output for each. It may take
several cycles to adequately train the network. At the end of each
cycle, the changes in the connections may be seen.
If things get hopelessly stuck, click on the randomize button. This
scrambles the connection strengths and allows you to start over.
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