However , even though the error surface of multi-layer networks are much more complicated , locally they can be approximated by a paraboloid .
Jump up ^ One may notice that multi-layer neural networks use non-linear activation functions , so an example with linear neurons seems obscure .
Even though the error surface of multi-layer networks are much more complicated , locally they can be approximated by a paraboloid .
Jump up ^ One may notice that multi-layer neural networks use non-linear activation functions , so an example with linear neurons seems obscure .