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Título del libro: Applications And Innovations In Intelligent Systems Xvi - Proceedings Of Ai 2008, The 28th Sgai International Conference On Innovative Techniques And Applications Of Artificial Intelligence
Título del capítulo: Recognition of swallowing sounds using time-frequency decomposition and limited receptive area neural classifier

Autores UNAM:
TETYANA BAYDYK;

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Autores externos:

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Idioma:
Inglés

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Año de publicación:
2009

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Palabras clave:

Classifier training; Continuous wavelet transforms; Efficiency and reliability; Feature selection and extractions; Lira neural classifiers; Short time Fourier transforms; Time frequency domain; Time-frequency decomposition; Extraction; Intelligent systems; Pattern recognition; Wavelet transforms; Neural networks

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Resumen:

In this paper we propose a novel swallowing sound recognition technique based on the limited receptive area (LIRA) neural classifier and time-frequency decomposition. Time-frequency decomposition methods commonly used in sound recognition increase dimensionality of the signal and require steps of feature selection and extraction. Quite often feature selection is based on a set of empirically chosen statistics, making the pattern recognition dependent on the intuition and skills of the investigator. A limited set of extracted features is then presented to a classifier. The proposed method avoids the steps of feature selection and extraction by delegating them to a limited receptive area neural (LIRA) classifier. LIRA neural classifier utilizes the increase in dimensionality of the signal to create a large number of random features in the time-frequency domain that assure a good description of the signal without prior assumptions of the signal properties. Features that do not provide useful information for separation of classes do not obtain significant weights during classifier training. The proposed methodology was tested on the task of recognition of swallowing sounds with two different algorithms of time-frequency decomposition, short-time Fourier transform (STFT) and continuous wavelet transform (CWT). The experimental results suggest high efficiency and reliability of the proposed approach. © 2009 Springer-Verlag London.

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Entidades citadas de la UNAM:

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Fuente:


ISBN:
9781848822146
Editorial:

Tipo de producto:
Conference Paper

DOI:
10.1007/978-1-84882-215-3-3