Can two different activation function be used at the same time in a Neural Network?

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Dr R Senthilkumar

my point of view, two different activation functions can affect network stability

Mala Babagana Gutti

Thanks @Senthilkumar

Fouad Amer

Only non-linear activation functions are useful between different layers. If you dont' apply a non-linear activation between two layers, you will basically be transforming both layers into one: w2(w1x + b1) + b2 = w3(x) + b3 which is still linear.

So, from what I understand from your statement, when two activation functions are involved, it will always be a linear activation function @Amer