微调数字FIR过器与灰狼优化,以达到峰值性能
Anand R1, Sathishkumar Samiappan2, M Prabukumar3
1Department of Electrical and Electronics Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India, 641112. r_anand2@cb.amrita.edu.
Scientific reports
|June 3, 2024
概括
这项研究使用进化算法优化了数字过器. 灰狼算法在设计有限冲动响应 (FIR) 过器方面表现出卓越的性能,实现了更高的精度和更快的执行时间.
科学领域:
- 数字信号处理 数字信号处理
- 计算智能是一种计算智能.
- 过器的设计设计
背景情况:
- 最佳的过器设计对于信号处理至关重要,其目标是平面传输带和高止带衰减.
- 有限冲动响应 (FIR) 过器被广泛使用,但它们的最佳设计带来了挑战.
研究的目的:
- 用自然灵感优化算法解决FIR过器设计问题.
- 为了比较灰狼优化 (GWO),乌搜索 (CS),粒子群优化 (PSO) 和基因算法 (GA) 对于 FIR 过器设计的有效性.
主要方法:
- 实施GWO,CS,PSO和GA来设计FIR低通,高通和带停止过器.
- 根据停止带衰减,传输带波纹和偏离所需响应来评估波器性能.
- 比较算法执行时间和实现全球最佳解决方案的能力.
主要成果:
- 灰狼优化算法在设计FIR过器方面表现优于其他方法.
- 与CS,PSO和GA相比,GWO带来了更高的设计精度和更短的执行时间.
- 所有测试的算法都能够实现FIR波器设计的最佳解决方案.
结论:
- 灰狼优化算法是设计数字FIR过器的高效方法.
- 在过器设计应用中,GWO提供了性能,精度和效率的卓越平衡.
- 灵感来自自然的算法为复杂的过器设计问题提供了强大的解决方案.
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