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.

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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.

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