Scholarlink

<p>Fractional calculus has increasingly become a robust framework for modeling complex systems in engineering, offering advantages over traditional integer-order methods through its ability to encapsulate memory and non-local dynamics. Fractional-order integrators, in particular, have found applications in control engineering, signal processing, and biomedical fields. Despite their theoretical benefits, the digital realization of such integrators–especially under real-time constraints–poses significant challenges. This paper presents a comparative analysis of three numerical approximation methods for the digital implementation of fractional-order integrators on Field-Programmable Gate Arrays (FPGAs): Simpson’s method, Tustin’s method, and the Grünwald-Letnikov method. By exploiting the parallelism and reconfigurability of FPGAs, the study evaluates these approaches in terms of numerical accuracy, convergence properties, and resource utilization, thereby providing insights into the trade-offs inherent in each method for real-time applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Resource-Efficient Design of High-Speed FIR Filter: Fractional-Order Integrator/Differentiator on FPGAs

  • 期刊论文

  • 发表日期：

    2026年4月9日

查看全文
  • Berke Akgul,
  • Emir Güler,
  • Hakan Ersoy,
  • Aslihan Kartci,
  • Umut Engin Ayten

摘要

Fractional calculus has increasingly become a robust framework for modeling complex systems in engineering, offering advantages over traditional integer-order methods through its ability to encapsulate memory and non-local dynamics. Fractional-order integrators, in particular, have found applications in control engineering, signal processing, and biomedical fields. Despite their theoretical benefits, the digital realization of such integrators–especially under real-time constraints–poses significant challenges. This paper presents a comparative analysis of three numerical approximation methods for the digital implementation of fractional-order integrators on Field-Programmable Gate Arrays (FPGAs): Simpson’s method, Tustin’s method, and the Grünwald-Letnikov method. By exploiting the parallelism and reconfigurability of FPGAs, the study evaluates these approaches in terms of numerical accuracy, convergence properties, and resource utilization, thereby providing insights into the trade-offs inherent in each method for real-time applications.