Segmentación de espectrograma de patrones por convolución de modelo-base aplicado a señales con ruido aditivo Article Swipe

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César U. Solis , Sergio Isaí Palomino-Reséndiz ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.29057/icbi.v12iespecial4.13171

El presente trabajo establece un método convolucional por segmentación de espectrograma para detectar señales discretizadas con un patrón espectral de interés y que está contaminada con ruido aditivo, donde la detección por espectrograma estándar tiende a no ser el procedimiento más eficiente. Para lograr dicho objetivo se propone una metodología de tres pasos: generación de un modelo-base de patrones de interés con características similares a identificar, extraer la norma de la transformada Gabor discreta de la señal a identificar en convolución con los patrones del modelo-base, umbralizar el resultado del paso anterior para limitar el contenido espectral del ruido e identificar los patrones resultantes. Se compara este método con los tradicionales de convolución de funciones seno/coseno (espectrograma) y se marcan las ventajas y desventajas de ambos. Para su validación se implementa código en Matlab 2024a del algoritmo propuesto. Finalmente se hacen comentarios de trabajos futuros sobre la identificación de señales de ondas gravitacionales inmersas en señales con ruido en los que se puede aplicar la metodología para encontrar dichos patrones.

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Type: article
Language: es
Landing Page: https://doi.org/10.29057/icbi.v12iespecial4.13171
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DOI: https://doi.org/10.29057/icbi.v12iespecial4.13171

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Title: Segmentación de espectrograma de patrones por convolución de modelo-base aplicado a señales con ruido aditivo

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Language: es

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Publication year: 2024

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Publication date: 2024-11-30

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Authors: César U. Solis, Sergio Isaí Palomino-Reséndiz

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Landing page: https://doi.org/10.29057/icbi.v12iespecial4.13171

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