The computation of complex functions such as the trigonometric and hyperbolic ones is usually performed either implying large lookup tables or by long software routines. However, the suitability of both solutions strongly depends on the specific application. For example, the former one, storing the results inside a memory, can be very fast and efficient when accuracy is not paramount, but it can lead to prohibitive area occupations. On the other hand, the latter solution exploits polynomial approximation to provide precise results, but it forces the processor to spend a large amount of time waiting for its completion. As a result, the two approaches cannot be adopted for high-accuracy and low-latency applications.