# Novel design strategy of multiplier-less low-pass finite impulse response filter using self-organizing random immigrants genetic algorithm

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## Abstract

Intelligent optimization techniques are playing a very vital role in solving a wide variety of problems of engineering and technology of late. In order to meet the challenges from various perspectives, researchers are always in favor of applying those approaches to get rid of numerous practical difficulties of concern. Digital signal processing, more specifically the design of digital filters in particular, has been immensely motivated and beneficiated by means of this amalgamation. In this communication, we have incorporated a recently proposed genetic optimization method, named as self-organizing random immigrants genetic algorithm, in multiplier-free finite impulse response filter (FIR) design algorithm. Our study has focused on the selection of optimum settlement of filter coefficients through the utilization of this population-based technique which results in power of two distribution of impulse response over a binary search space. The performance of our designed filter has been thoroughly analyzed by a number of design parameters of interest and compared with other state-of-the-art multiplier-less FIR models. It has been observed that the proposed approach outperforms the other designs by a considerably large margin in those areas of signal processing where the reduction in hardware cost is the biggest challenge.

## Keywords

Finite duration impulse response (FIR) filter Multiplier-less architecture Power-of-two terms Replacement rate Self-organizing random immigrants genetic algorithm (SORIGA)## References

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