# Is it still called linear separation with a layer of more than 1 neuron

A single neuron will be able to do linear separation. For example, XOR simulator network:

x1 --- n1.1
\  /    \
\/      \
n2.1
/\      /
/  \    /
x2 --- n1.2


Where x1, x2 are the 2 inputs, n1.1 and n1.2 are the 2 neurons in hidden layer, and n2.1 is the output neuron.

The output neuron n2.1 does a linear separation. How about the 2 neurons in hidden layer?

Is it still called linear separation (at 2 nodes and join the 2 separation lines)? or polynomial separation of degree 2?

I'm confused about how it's called because there are curvy lines in this wiki article: https://en.wikipedia.org/wiki/Overfitting