A neural network classifier for notch filter classification of sound-source elevation in a mobile robot

John C. Murray, Harry R. Erwin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

An important aspect of all robotic systems is sensing and there are many sensing modalities used including vision, tactile, olfactory and acoustics to name a few. This paper presents a robotic system for sensing in acoustics, specifically in elevation localization. The model presented is a two-stage model incorporating spectral analysis using artificial pinna and an artificial neural network for classification and elevation estimation. The spectral classifier uses notch filters to analyze changes in attenuation of certain frequencies with elevation. This paper shows how using the spectral output of a signal generated by an artificial pinna can be classified by a feed-forward backpropagation neural network to estimate the elevation of a sound-source.

Original languageEnglish
Title of host publication2011 International Joint Conference on Neural Networks, IJCNN 2011
PublisherIEEE
Pages763-769
Number of pages7
ISBN (Electronic)9781457710865, 9781424496372
ISBN (Print)9781424496358
DOIs
Publication statusPublished - 3 Oct 2011
Externally publishedYes
Event2011 International Joint Conference on Neural Network, IJCNN 2011 - San Jose, CA, United States
Duration: 31 Jul 20115 Aug 2011

Publication series

NameProceedings of the International Joint Conference on Neural Networks
PublisherIEEE
ISSN (Print)2161-4393
ISSN (Electronic)2161-4407

Conference

Conference2011 International Joint Conference on Neural Network, IJCNN 2011
Country/TerritoryUnited States
CitySan Jose, CA
Period31/07/115/08/11

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