Skip to main navigation Skip to search Skip to main content

Co-evolution Genetic Algorithm Approximation Technique for ROM-Less Digital Synthesizers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new polynomial approximation technique is presented using the concept of co-evolution genetic algorithm. In the proposed technique each polynomial coefficient is considered as a set of independent populations rather being considered as one. These populations co-evolve as they try to optimize the spurious-free dynamic range (SFDR) of a direct digital frequency synthesizer (DDFS). Obtained SFDR from these optimized polynomials have outperformed that of the polynomials evaluated using deterministic approaches. Optimized polynomials for 2nd and 3rd order approximations have achieved 62 dBc and 82 dBc after hardware implementation. Also in the paper a simple genetic algorithm has been explained for optimal pipeline level insertion for a specific hardware implementation of polynomial functions in FPGA platforms.

Original languageEnglish
Title of host publicationProceedings of the 37th International Conference on Advanced Information Networking and Applications (AINA-2023), Volume 3
EditorsLeonard Barolli
Place of PublicationSwitzerland
PublisherSpringer Cham
Pages573-584
Volume3
ISBN (Print)9783031286933, 9783031286940
DOIs
Publication statusPublished - 15 Mar 2023
EventAINA 2023: The 37th International Conference on Advanced Information Networking and Applications - Federal University of Juiz de Fora, Brazil, Brazil
Duration: 29 Mar 202331 Mar 2023

Publication series

NameLecture Notes in Networks and Systems
Number655

Conference

ConferenceAINA 2023: The 37th International Conference on Advanced Information Networking and Applications
CityBrazil
Period29/03/2331/03/23

Fingerprint

Dive into the research topics of 'Co-evolution Genetic Algorithm Approximation Technique for ROM-Less Digital Synthesizers'. Together they form a unique fingerprint.

Cite this