Abstract

The construction of a meaningful metric between acoustic responses which respects the source locations, is addressed. By comparing three alternative distance measures, we verify the existence of the acoustic manifold and give an insight into its nonlinear structure. From such a geometric view point, we demonstrate the limitations of linear approaches to infer physical adjacencies. Instead, we introduce the diffusion framework, which combines local and global processing in order to find an intrinsic nonlinear embedding of the data on a low dimensional manifold. We present the diffusion distance which is related to the geodesic distance on the manifold. In particular, simulation results demonstrate the ability of the diffusion distance to organize the samples according to the source direction of arrival (DOA).

Original languageEnglish
Title of host publicationLatent Variable Analysis and Signal Separation - 12th International Conference, LVA/ICA 2015, Proceedings
EditorsZbynĕk Koldovský, Emmanuel Vincent, Arie Yeredor, Petr Tichavský
PublisherSpringer Verlag
Pages203-210
Number of pages8
ISBN (Print)9783319224817
DOIs
StatePublished - 2015
Event12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2015 - Liberec, Czech Republic
Duration: 25 Aug 201528 Aug 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9237

Conference

Conference12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2015
Country/TerritoryCzech Republic
CityLiberec
Period25/08/1528/08/15

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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