Approximating functions for embedded and ASIC applications

Abstract

Often embedded programmers and application specific integrated circuit (ASIC) designers are frustrated by the inability to realize near floating-point accuracy. in a fixed-point application. The problem is not limited to function approximation but also impacts FIR filter design. In this paper we examine the problem of approximating a known function on a closed interval and show that a genetic algorithm (GA) may be used to obtain results superior to those obtained by implementing floating-point algorithms, such as Taylor series and Chebyshev polynomials, in fixed-point directly.