0000000000393902

AUTHOR

José V. Francés Villora

showing 2 related works from this author

Versatile Direct and Transpose Matrix Multiplication with Chained Operations: An Optimized Architecture Using Circulant Matrices

2016

With growing demands in real-time control, classification or prediction, algorithms become more complex while low power and small size devices are required. Matrix multiplication (direct or transpose) is common for such computation algorithms. In numerous algorithms, it is also required to perform matrix multiplication repeatedly, where the result of a multiplication is further multiplied again. This work describes a versatile computation procedure and architecture: one of the matrices is stored in internal memory in its circulant form, then, a sequence of direct or transpose multiplications can be performed without timing penalty. The architecture proposes a RAM-ALU block for each matrix c…

Cycles per instructionBlock matrix020206 networking & telecommunications02 engineering and technologyParallel computingMatrix chain multiplicationMatrix multiplication020202 computer hardware & architectureTheoretical Computer ScienceMatrix (mathematics)Computational Theory and MathematicsHardware and ArchitectureTranspose0202 electrical engineering electronic engineering information engineeringMultiplicationHardware_ARITHMETICANDLOGICSTRUCTURESArithmeticCirculant matrixSoftwareMathematicsIEEE Transactions on Computers
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Ventricular Fibrillation detection using time-frequency and the KNN classifier without parameter extraction

2017

[ES] Este trabajo propone la detección de FV y su discriminación de TV y otros ritmos cardiacos basándose en la representación tiempo-frecuencia del ECG y su conversión en imágen como entrada a un clasificador de vecinos más cercanos (KNN) sin necesidad de extracción de parámetros adicionales. Tres variantes de datos de entrada al clasificador son evaluados. Los resultados clasifican la señal en cuatro clases diferentes: ’Normal’ para latidos con ritmo sinusal, ’FV’ para fibrilación ventricular, ’TV’ para taquicardia ventricular y ’Otros’ para el resto de ritmos. Los resultados para detección de FV mostraron 88,27% de sensibilidad y 98,22% de especificidad para la entrada de imágen equivale…

medicine.medical_specialtyBiomedical systemsGeneral Computer ScienceSeñales no estacionarias0206 medical engineeringTime-frequency representationClasificación02 engineering and technologyElectrocardiographic signalsVentricular tachycardiaNon-stationary signalsImage analysisAnálisis de imágenesInternal medicine0202 electrical engineering electronic engineering information engineeringmedicineSinus rhythmSistemas biomédicosbusiness.industrySeñales ElectrocardiográficasClassificationmedicine.disease020601 biomedical engineeringRepresentación tiempo-frecuenciaControl and Systems EngineeringSignal parameterVentricular fibrillationCardiology020201 artificial intelligence & image processingbusinessRevista Iberoamericana de Automática e Informática industrial
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