Binary threshold unit ($z=H({\sum }_i{w}_i{z}_i-\theta )$)

A binary threshold unit outputs one when its weighted input reaches its threshold and zero otherwise. Its hard threshold is not differentiable, so ordinary backpropagation cannot directly train the exact threshold model. Smooth activation functions can approximate its computation.