Optimal design of digital FIR filters based on back propagation neural network

DOI Web Site 29 References
  • Yang Jiyao
    College of Electrical Engineering Guizhou University
  • Yang Hao
    College of Electrical Engineering Guizhou University
  • Yang Xing
    College of Electrical Engineering Guizhou University
  • Yang Jiansheng
    College of Electrical Engineering Guizhou University

Abstract

<p>In the traditional digital finite impulse response (FIR) filter design, there exist some limitations. For instance, unwanted signals cannot be filtered out by using these FIR filters. Therefore, to break these limitations, this paper proposes an optimization method for designing digital FIR filters based on the back propagation neural network (BPNN) algorithm. Firstly, an amplitude response model has been established based on the linear properties of the digital FIR filters. Then, the BPNN algorithm has been used to minimize the estimation error between the ideal and the actual amplitude response such that the optimal coefficients of the digital FIR filter can be obtained. Finally, several design examples are used to verify the performance of our proposed optimal design based on BPNN. The simulation results show that, compared with the optimal designs based on the sequential and rectangular window, our proposed optimal design based on BPNN can achieve better filtering effectiveness but at the cost of larger computational complexity.</p>

Journal

  • IEICE Electronics Express

    IEICE Electronics Express 20 (1), 20220491-20220491, 2023-01-10

    The Institute of Electronics, Information and Communication Engineers

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