java - Neural network activation function -

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i've had time building own ann library, i'm having difficulties understanding behaviors.

here activation functions coded:

doublefunction<double> sigmoid = x -> 1 / (1 + math.exp(-x)); doublefunction<double> sigmoidder = x -> {     double s = sigmoid.apply(x);     return s * (1 - s); };  doublefunction<double> tanh = math::tanh; doublefunction<double> tanhder = x -> 1. - math.pow(tanh.apply(x), 2);  doublefunction<double> relu = x -> math.max(0, x); doublefunction<double> reluder = x -> {     if (x < 0)         return 0;     return 1; };  doublefunction<double> softplus = x -> math.log(1 + math.exp(x));

in code i'm selecting pair serve activation function (+ derivative).

none of functions convege solution (i'm trying net learn xor operator) tanh function , derivative.

note: using bias neuron each layer outputs constant 1.

i've checked this out apparently i'm missing fundamental here.

does care enlighten me?


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