Multi-Objective Genetic Algorithms for computing Fast Fourier Transform for evolving Smart Sensors devices using Field Programmable gate arrays

This research explores the use of Fast Fourier Transform (FFT) in the design of smart sensors and various other portable telecommunication devices. Literature reveals thatgenetic algorithms play an increasingly important role in the computing FFT for the design and implementation ofthe foresaid devices. In this paper, a multi- objectivegenetic algorithm for computing Fast Fourier Transform for evolving smart sensor devices has been designed andsimulated in software in a field programmable gateway array using Altera Quartus II 13.0. Programmable logic units, ( Luts-representing genes in a chromosome) weredesigned using schematic /block diagrams and hardware description language and they were encoded intochromosomes and then optimized using field programmable gate arrays (FPGA) to achieve desired goals of portability and low energy consumption. Theperformance of our design was evaluated using Altera Quartus II Powerplay power analyser tool in terms of core static thermal power dissipation, core dynamic thermalpower dissipation and input and output thermal power dissipation. The model was also evaluated in terms offunctional correctness and portability. The results show significant improvements in all performance measures.

Multi-Objective Genetic Algorithms for computing Fast Fourier Transform for evolving Smart Sensors devices using Field Programmable gate arrays Keywords:

Genetic algorithm , Programmable logic unit (Luts) , Fast Fourier Transform , Field programmable gate Array