Near field acoustic localization under unfavorable conditions using feedforward neural network for processing time difference of arrival

作者：

Highlights：

• Providing guidelines for practical implementation of neural networks in near-field sound source localization.

• Obtained optimal sensors setups.

• Obtaining optimal network configuration.

• Obtaining optimal training parameters.

• Proving effectiveness of feedforward neural network in solving hyperbolic positioning problem under the uncertainties.

摘要

•Providing guidelines for practical implementation of neural networks in near-field sound source localization.•Obtained optimal sensors setups.•Obtaining optimal network configuration.•Obtaining optimal training parameters.•Proving effectiveness of feedforward neural network in solving hyperbolic positioning problem under the uncertainties.

论文关键词：Processing time difference,Acoustic source localization,Time difference of arrival,Feedforward neural network,Artificial intelligence

论文评审过程：Received 23 June 2016, Revised 30 October 2016, Accepted 20 November 2016, Available online 21 November 2016, Version of Record 1 December 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.11.030