Spiking neural network for sound localization using microphone array

M. Faraji, S. Shouraki, Ensieh Iranmehr
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引用次数: 8

Abstract

Sound source localization is very useful in various fields of engineering applications. Due to remarkable ability of humans for sound source localization, this paper describes a simple biological inspired model based on spiking neural network for localizing sound source. In this paper, a simple method using analog and digital combinational circuits is proposed for generating spikes. Because of simplicity of the proposed generating spikes method, in this paper, microphone array is utilized instead of using two microphones in order to increase accuracy. Then, a neural structure based on spiking neural network is proposed which works by means of microphone's signals. This structure is designed in way that can be implemented on Field Programming Gate Array (FPGA) properly. Simulation results show that implementing of this model for different types of microphone array is not only very simple, but also shows high accuracy of localizing sound source.
基于麦克风阵列的脉冲神经网络声音定位
声源定位在工程应用的各个领域都是非常有用的。由于人类对声源定位的能力非常强,本文提出了一种简单的基于脉冲神经网络的生物启发声源定位模型。本文提出了一种利用模拟和数字组合电路产生尖峰的简单方法。由于本文提出的产生尖峰的方法简单,为了提高精度,本文采用麦克风阵列代替两个麦克风。在此基础上,提出了一种基于尖峰神经网络的基于麦克风信号的神经网络结构。这种结构设计的方式可以在现场编程门阵列(FPGA)上适当地实现。仿真结果表明,该模型适用于不同类型的传声器阵列,不仅实现简单,而且声源定位精度高。
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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