Cascade-forward neural network adding new units

For Cascade correlation network I found this definition: We add hidden units to the network one by one. Each new unit therefore adds a new one-unit "layer" to the network, unless some of its incoming weights happen to be zero. This is confuse me beacuse when I run Cascade network in MATLAB it looks like there is 10 neurons from beggining for example and I am not sure if it's the maximum of neurons only and it's really adding one by one during learning or there is 10 fixed neurons from beggining. How it works? Thank you.

Answer 1

[Greg Heath]

As answered in your previous post.

Despite the name, these are different networks.

Hope this helps.

Greg

[Chris P]

This doesn't answer the question