Study on Optimal Design of High-Order FIR Filter with
Multi-Band Stop Based on BP Neural Network
Abstract: This paper improves the traditional neural network and conquers its disadvantages of the slow convergence speed and the low learning efficiency with cosine basis functions as output functions of neural network unit. It studies on the amplitude-frequency characteristic of the FIR filters with linear phase by putting up models of neural network based on the cosine basis functions, and drawing the conclusion of relationship between them. The simulation results show that the algorithm has advantages over the design field of high-order FIR filter with multi-band stop.
文章引用: 张春龙 , 李德超 , 张玉环 (2014) 基于BP神经网络的高阶FIR多阻带滤波器优化设计。 电力与能源进展， 2， 1-5. doi: 10.12677/AEPE.2014.21001
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