Power-of-two adaptive filters using tabu search

Digital filters with power-of-two or a sum of power-of-two coefficients can be built using simple and fast shift registers instead of slower floating-point multipliers, such a strategy can reduce both the VLSI silicon area and the computational time. Due to the quantization and the nonuniform distribution of the coefficients through their domain, in the case of adaptive filters, classical steepest descent based approaches cannot be successfully applied. Methods for adaptation processes, as in the least mean squares (LMS) error and other related adaptation algorithms, can actually lose their convergence properties. In this work, we present a customized Tabu Search (TS) adaptive algorithm that works directly on the power-of-two filter coefficients domain, avoiding any rounding process. In particular, we propose TS for a time varying environment, suitable for real time adaptive signal processing. Several experimental results demonstrate the effectiveness of the proposed method.