What is the 'order' of a perceptron

A few simple marks for those who know the answer.

I'm doing revision for开发者_如何学运维 exams at the moment and one of the past questions is:

What is meant by the order of a perceptron?

I can't find any information about this in my lecture notes, and even google seems at a loss.

My guess is that the order is the number of layers in a neural network, but this doesn't seem quite right.

If you want to evaluate the order or cardinality of a multilayered NN you should consider just the number of inner layer as input and output layer are not considered belonging to the cardinality of the NN topology. For example a NN with 2 inner layer has order=2.

The funniest thing is that more than one layer is, most of the times, unusefull neither for performance neither for training.

Order of approximation in the learning algorithm. See orders of optimization algorithms.