machine learning - simple perceptron model and XOR -



machine learning - simple perceptron model and XOR -

sorry maintain asking here. study hard ready reply questions too!

many papers , articles claim there no restriction on choosing activation functions mlp.

it seems matter 1 fits given condition.

and articles mathematically proven simple perceptron can not solve xor problem.

i know simple perceptron model used utilize step function activation function.

but if doesn't matter activation function use, using

f(x)=1 if |x-a|<b f(x)=0 if |x-a|>b

as activation function works on xor problem. (for 2input 1output no hidden layer perceptron model)

i know using artificial functions not learning model. if works anyway, why articles proven doesn't work?

does article means simple perceptron model 1 using step function? or activation function simple perceptron has step function unlike mlp? or wrong?

in general, problem non-differentiable activation functions (like 1 proposed) cannot used back-propagation , other techniques. propagation convenient way estimate right threshold values (a , b in example). popular activation functions selected such approximate step behaviour while remaining differentiable.

machine-learning neural-network xor perceptron

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