General‐purpose DSP processors, application‐specific processors, and algorithm‐specific processors are used to implement different types of DSP systems or subsystems. They are typically used in applications involving complex and irregular algorithms while application‐specific processors provide lower unit cost and higher performance for a specific application, particularly when the volume of production is high. Most DSP applications use fractional arithmetic instead of integer arithmetic. Multimedia and communication applications involve real‐time audio and video/image processing which very often require sum‐of‐products (SOP) computation. The need of computing non‐linear functions arises in many different applications. The straightforward method of approximating an elementary function is to just store the values in a look‐up table typically leads to large tables, even though the resulting area from standard cell synthesis grows slower than the number of memory bits. It is of interest to find ways to approximate elementary functions using a trade‐off between arithmetic operations and look‐up tables.