Using evolutionary computing technology to improve algorithm performance innovation
The research background of improving algorithm performance by using evolutionary computing technology stems from the demand of signal processing and optimization algorithms.As an important signal processing tool, fast Fourier transform (FFT) can calculate discrete Fourier transform efficiently, and is widely used in digital signal processing, communication system and image processing.As an optimization algorithm simulating natural selection and genetic mechanism, genetic algorithm is combined with FFT to optimize the performance of FFT algorithm by adjusting key parameters, so as to improve the effect of signal processing and spectrum analysis.This research not only helps to explore the application of optimization algorithms in signal processing, but also provides innovative ideas and methods for improving the efficiency and accuracy of signal processing algorithms.
Authors
- K. F. Chang (ORCID: https://orcid.org/0009-0000-3638-4219)
- Longqing Zhang (ORCID: https://orcid.org/0000-0002-3991-7604)
- Bianping Su
- Yanfen Fang (ORCID: https://orcid.org/0000-0002-9245-4856)
- Qian Chen (ORCID: https://orcid.org/0000-0002-3070-1057)
- Xinwei Zhang (ORCID: https://orcid.org/0000-0002-3690-3127)
- Hongming Chen (ORCID: https://orcid.org/0000-0003-1231-7331)
- Jingyuan Ceng
- Changan Chen (ORCID: https://orcid.org/0000-0003-3990-6873)
Institutions
- Guangdong University of Technology (CN)
- Zhejiang Ocean University (CN)
- Guangdong Polytechnic of Science and Technology (CN)
- Guangdong Institute of Intelligent Manufacturing (CN)
- Central Academy of Fine Arts (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Proceedings Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.55092/pcs20250003
- Primary Topic
- Evolutionary Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Strong
- Guangdong University of Science and Technology