DCT-compressive sampling of multifrequency sparse audio signals

dc.contributor.authorRodolfo Moreno-Alvarado
dc.contributor.authorMauricio Martínez-García
dc.contributor.authorMariko Nakano-Miyatake
dc.contributor.authorHéctor Pérez-Meana
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T14:45:25Z
dc.date.available2026-03-22T14:45:25Z
dc.date.issued2014
dc.descriptionCitaciones: 19
dc.description.abstractIn this paper, we propose to apply the discrete cosine transform (DCT) and the compressive sampling (CS) techniques to audio signal compression. Using spectral analysis and the properties of the DCT, we can treat audio signals as sparse signals in the frequency domain. This is especially true for sounds representing tones. Thus, we propose the use of DCT as a preprocessor in order to sparsely represent a signal in the frequency domain, combined with CS to obtain an efficient representation of the signals. We show that the subsequent application of CS represents our signals with less information than the well-known sampling theorem.
dc.identifier.doi10.1109/latincom.2014.7041859
dc.identifier.urihttps://doi.org/10.1109/latincom.2014.7041859
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/48363
dc.language.isoen
dc.sourceInstituto Politécnico Nacional
dc.subjectDiscrete cosine transform
dc.subjectComputer science
dc.subjectPreprocessor
dc.subjectModified discrete cosine transform
dc.subjectSampling (signal processing)
dc.subjectSIGNAL (programming language)
dc.subjectFrequency domain
dc.subjectSpeech recognition
dc.subjectTransform coding
dc.subjectCompressed sensing
dc.titleDCT-compressive sampling of multifrequency sparse audio signals
dc.typearticle

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