Novel algorithms for word-length optimization

Digital signal processing applications are specified with floating-point data types but they are usually implemented in embedded systems with fixed-point arithmetic to minimize cost and power consumption. The floating-to-fixed point conversion requires an optimization algorithm to determine a combination of optimum word-length for each operator. This paper proposes new algorithms based on Greedy Randomized Adaptive Search Procedure (GRASP): accuracy-based GRASP and accuracy/cost-based GRASP. Those algorithms are iterative stochastic local searches and result in the best result through many test cases, including IIR, NLMS and FFT filters.