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A Diversity Controlled Genetic Algorithm for Optimization of FRM Digital Filters over DBNS Multiplier Coefficient Space

This paper presents a novel diversity controlled (DC) genetic algorithm (GA) for the optimization of frequency-response masking (FRM) FIR digital filters over the double base number system (DBNS) multiplier coefficient space. The use of DBNS multiplier coefficients reduces the complexity and power consumption in the hardware implementation of the resulting FRM FIR digital filters. A direct application of GAs to the design of FRM FIR digital filters may result in chromosomes which do not conform to the DBNS format due to the underlying crossover and mutation operations. The proposed algorithm uses a DBNS based indexed look-up table (LUT) to ensure generation of valid DBNS multiplier coefficients through out the course of genetic optimization. An application example is given for the design of an FRM FIR lowpass digital filter. The resulting FIR digital filter outperforms a corresponding infinite-precision digital filter obtained by using the Parks-McClellan technique.