A unit step activation function is a much-used feature in neural networks. The output assumes value 0 for negative argument and 1 for positive argument. The function is as follows:
The range is between (0,1) and the output is binary in nature. These types of activation functions are useful for binary schemes. When we want to classify an input model in one of two groups, we can use a binary compiler with a unit step activation function. A unit step activation function is shown in the following figure:
