# Can residual neural networks use other activation functions different from ReLU?

In many diagrams, as seen below, residual neural networks are only depicted with ReLU activation functions, but can residual NNs also use other activation functions, such as the sigmoid, hyperbolic tangent, etc.?

The problem with certain activation functions, such as the sigmoid, is that they squash the input to a finite interval (i.e. they are sometimes classified as saturating activation functions). For example, the sigmoid function has codomain $$[0, 1]$$, as you can see from the illustration below.