A design of adaptive neural filter banks with filter neuron

Juwon Lee, Won-Geun Jung, Gun-Ki Lee
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Abstract

In this study, we propose that the new filter bank that is an adaptive filter bank using neural networks in time domain. Also, we propose a filter neuron as band pass filter (BPF) with hamming window, the structure and algorithm for filter banks. The performance of neural filter banks is shown from two examples. It shows its characteristics such as the simple structure and a higher speed processing compared to traditional methods (filter banks in frequency domain, etc.). In many applications, the proposed method will provide a higher performance to feature detection of signals in time domain.
基于滤波神经元的自适应神经滤波器组的设计
在本研究中,我们提出了一种新的滤波器组,即在时域上使用神经网络的自适应滤波器组。此外,我们还提出了一种带汉明窗的带通滤波器(BPF),以及滤波器组的结构和算法。通过两个实例说明了神经滤波器组的性能。与传统方法(频域滤波器组等)相比,该方法具有结构简单、处理速度快等特点。在许多应用中,该方法可以提供更高的时域信号特征检测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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