S-shaped. E.g. Gyrosigma and some species of Nitzschia.
In neural networks, the use of a sigmoid transfer function (as opposed to a step function) allows the function to be differentiated and thus allows back-propagation of values for automated learning.
Monotonic S-shaped function that maps numbers in the interval (-∞,∞) to a finite interval such as (-1,+1) or (0,1).
Many natural processes and complex system learning curves display a history dependent progression from small beginnings that accelerates and approaches a climax over time. For lack of complex descriptions a sigmoid function is often used.