PUBLICACIÓN

Towards robust features in voice disease diagnosis: MFCCS VS. PNCCS

ACCEDER A LA PUBLICACIÓN: Scopus Orcid

Madruga M., Campos-Roca Y., Perez C.J.

2019 Models and Analysis of Vocal Emissions for Biomedical Applications - 11th International Workshop, MAVEBA 2019

CITAS

0

EID

2-s2.0-85086603520

ISBN

9788864539614

BIBTEX

@article{Pérez2019,title = {Towards robust features in voice disease diagnosis: MFCCS VS. PNCCS},journal = {Models and Analysis of Vocal Emissions for Biomedical Applications - 11th International Workshop, MAVEBA 2019},year = {2019},pages = {103-106},author = {Madruga, M. and Campos-Roca, Y. and P{\'e}rez, C.J.}}

AUTORES DE LA UEX

Carlos Javier Pérez Sánchez
Yolanda Campos Roca

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Aplicación De Técnicas De Aprendizaje Colaborativo Basado En Proyectos A La Docencia De Estadística En Ciencias Veterinarias
Análisis Bayesiano De Datos Mal Clasificados En Presencia De Covariables
Aplicación De Técnicas De Aprendizaje Colaborativo Basado En Proyectos A La Docencia De Estadística En Ciencias Veterinarias
Análisis Bayesiano De Datos Mal Clasificados En Presencia De Covariables
Inference On Exponential Families With Mixture Of Prior Distributions
Análisis Bayesiano De Datos Mal Clasificados En Presencia De Covariables
Inference On Exponential Families With Mixture Of Prior Distributions
Local Parametric Sensitivity For Mixture Models Of Lifetime Distributions
Inference On Exponential Families With Mixture Of Prior Distributions
Local Parametric Sensitivity For Mixture Models Of Lifetime Distributions
Bayesian Analysis Of A Generalized Lognormal Distribution
Local Parametric Sensitivity For Mixture Models Of Lifetime Distributions
Bayesian Analysis Of A Generalized Lognormal Distribution
Bayesian Robustness For Decision Making Problems: Applications In Medical Contexts
Bayesian Analysis Of A Generalized Lognormal Distribution
Bayesian Robustness For Decision Making Problems: Applications In Medical Contexts
Modeling Experts' Opinions By Using Bayesian Mixture Models For A Subclass Of The Exponential Family
Bayesian Robustness For Decision Making Problems: Applications In Medical Contexts
Modeling Experts' Opinions By Using Bayesian Mixture Models For A Subclass Of The Exponential Family
Application Of A Generalized Lognormal Distribution To Engineering Data Fitting
Modeling Experts' Opinions By Using Bayesian Mixture Models For A Subclass Of The Exponential Family
Application Of A Generalized Lognormal Distribution To Engineering Data Fitting
A Logistic Regression-Based Pairwise Comparison Method To Aggregate Preferences
Application Of A Generalized Lognormal Distribution To Engineering Data Fitting
A Logistic Regression-Based Pairwise Comparison Method To Aggregate Preferences
Efficient Generation Of Random Vectors By Using The Ratio-Of-Uniforms Method With Ellipsoidal Envelopes
A Logistic Regression-Based Pairwise Comparison Method To Aggregate Preferences
Efficient Generation Of Random Vectors By Using The Ratio-Of-Uniforms Method With Ellipsoidal Envelopes
A Bayesian Model For Multinomial Sampling With Misclassified Data
Efficient Generation Of Random Vectors By Using The Ratio-Of-Uniforms Method With Ellipsoidal Envelopes
A Bayesian Model For Multinomial Sampling With Misclassified Data
An Interactive Tool For Mpeg-1 Audio Compression
A Bayesian Model For Multinomial Sampling With Misclassified Data
An Interactive Tool For Mpeg-1 Audio Compression
La Estad穩stica Visual Como Herramienta Did獺ctica En La Asignatura Matem獺ticas De Una Licenciatura En Veterinaria
An Interactive Tool For Mpeg-1 Audio Compression
La Estad穩stica Visual Como Herramienta Did獺ctica En La Asignatura Matem獺ticas De Una Licenciatura En Veterinaria
Una Generalizaci籀n De La Lognormal: Ajuste De Tiempos De Vida
La Estad穩stica Visual Como Herramienta Did獺ctica En La Asignatura Matem獺ticas De Una Licenciatura En Veterinaria
Una Generalizaci籀n De La Lognormal: Ajuste De Tiempos De Vida
Rage: A Java-Implemented Visual Random Generator
Una Generalizaci籀n De La Lognormal: Ajuste De Tiempos De Vida
Rage: A Java-Implemented Visual Random Generator
Bayesian Analysis Of Finite Mixtures Of Multinomial And Negative-Multinomial Distributions
Rage: A Java-Implemented Visual Random Generator
Bayesian Analysis Of Finite Mixtures Of Multinomial And Negative-Multinomial Distributions
Bayesian Analysis Of Finite Mixture Models Of Distributions From Exponential Families
Bayesian Analysis Of Finite Mixtures Of Multinomial And Negative-Multinomial Distributions
Bayesian Analysis Of Finite Mixture Models Of Distributions From Exponential Families
Mcmc-Based Local Parametric Sensitivity Estimations
Bayesian Analysis Of Finite Mixture Models Of Distributions From Exponential Families
Mcmc-Based Local Parametric Sensitivity Estimations
Sensitivity Estimations For Bayesian Inference Models Solved By Mcmc Methods
Mcmc-Based Local Parametric Sensitivity Estimations
Sensitivity Estimations For Bayesian Inference Models Solved By Mcmc Methods
G-Band Metamorphic Hemt-Based Frequency Multipliers
Sensitivity Estimations For Bayesian Inference Models Solved By Mcmc Methods
G-Band Metamorphic Hemt-Based Frequency Multipliers
Quasi-Random Sampling Importance Resampling
G-Band Metamorphic Hemt-Based Frequency Multipliers
Quasi-Random Sampling Importance Resampling
A D-Band Frequency Doubler Mmic Based On A 100-Nm Metamorphic Hemt Technology
Quasi-Random Sampling Importance Resampling
A D-Band Frequency Doubler Mmic Based On A 100-Nm Metamorphic Hemt Technology
Simulación Hacia Adelante Ponderada En Diseños Secuenciales Bayesianos
A D-Band Frequency Doubler Mmic Based On A 100-Nm Metamorphic Hemt Technology
Simulación Hacia Adelante Ponderada En Diseños Secuenciales Bayesianos
Aproximación De Distribuciones A Posteriori Utilizando El Método De Cociente De Uniformes
Simulación Hacia Adelante Ponderada En Diseños Secuenciales Bayesianos
Aproximación De Distribuciones A Posteriori Utilizando El Método De Cociente De Uniformes
Millimeter-Wave Active Mmic Frequency Multipliers
Aproximación De Distribuciones A Posteriori Utilizando El Método De Cociente De Uniformes
Millimeter-Wave Active Mmic Frequency Multipliers
Comparison Of Two Clinical Scales For Causality Assessment In Hepatotoxicity
Millimeter-Wave Active Mmic Frequency Multipliers
Comparison Of Two Clinical Scales For Causality Assessment In Hepatotoxicity
A Simplified Broad-Band Large-Signal Nonquasi-Static Table-Based Fet Model
Comparison Of Two Clinical Scales For Causality Assessment In Hepatotoxicity
A Simplified Broad-Band Large-Signal Nonquasi-Static Table-Based Fet Model
Extraction Of Transistor Large Signal Models From Vector Nonlinear Network Analyzers
A Simplified Broad-Band Large-Signal Nonquasi-Static Table-Based Fet Model
Extraction Of Transistor Large Signal Models From Vector Nonlinear Network Analyzers
Direct Extraction Of Nonlinear Fet Q—v Functions From Time Domain Large Signal Measurements
Extraction Of Transistor Large Signal Models From Vector Nonlinear Network Analyzers
Direct Extraction Of Nonlinear Fet Q—v Functions From Time Domain Large Signal Measurements
38/76 Ghz Phemt Mmic Balanced Frequency Doublers In Coplanar Technology
Direct Extraction Of Nonlinear Fet Q—v Functions From Time Domain Large Signal Measurements
38/76 Ghz Phemt Mmic Balanced Frequency Doublers In Coplanar Technology
An Optimized 25.5-76.5 Ghz Phemt-Based Coplanar Frequency Tripler
38/76 Ghz Phemt Mmic Balanced Frequency Doublers In Coplanar Technology
An Optimized 25.5-76.5 Ghz Phemt-Based Coplanar Frequency Tripler
Lmds Up-And Down-Converter Mmic
An Optimized 25.5-76.5 Ghz Phemt-Based Coplanar Frequency Tripler
Lmds Up-And Down-Converter Mmic
Simulación Utilizando El Muestreo Gibbs
Lmds Up-And Down-Converter Mmic
Simulación Utilizando El Muestreo Gibbs
Direct Extraction Of Nonlinear Fet C-V Functions From Time Domain Large Signal Measurements
Simulación Utilizando El Muestreo Gibbs
Direct Extraction Of Nonlinear Fet C-V Functions From Time Domain Large Signal Measurements
Coplanar Phemt Mmic Frequency Multipliers For 76-Ghz Automotive Radar
Direct Extraction Of Nonlinear Fet C-V Functions From Time Domain Large Signal Measurements
Coplanar Phemt Mmic Frequency Multipliers For 76-Ghz Automotive Radar
Accurate Extraction Of Nonlinear Intrinsic Transistor Current State Functions From Large Signal Waveform Measurements
Coplanar Phemt Mmic Frequency Multipliers For 76-Ghz Automotive Radar
Accurate Extraction Of Nonlinear Intrinsic Transistor Current State Functions From Large Signal Waveform Measurements
Direct Extraction Of Nonlinear Fet I-V Functions From Time Domain Large Signal Measurements
Accurate Extraction Of Nonlinear Intrinsic Transistor Current State Functions From Large Signal Waveform Measurements
Direct Extraction Of Nonlinear Fet I-V Functions From Time Domain Large Signal Measurements
Experimental Demonstration And Cad Investigation Of Class B Hfet Transistor Operation At Microwave Frequencies
Direct Extraction Of Nonlinear Fet I-V Functions From Time Domain Large Signal Measurements
Experimental Demonstration And Cad Investigation Of Class B Hfet Transistor Operation At Microwave Frequencies
Accurate Hemt Model Extraction And Validation In Class A And B Bias Points Using A Full Two-Port Large Signal On-Wafer Measurement System
Experimental Demonstration And Cad Investigation Of Class B Hfet Transistor Operation At Microwave Frequencies
Accurate Hemt Model Extraction And Validation In Class A And B Bias Points Using A Full Two-Port Large Signal On-Wafer Measurement System
Accurate Hemt Model Extraction And Validation In Class A And B Bias Points Using A Full Two-Port Large Signal On-Wafer Measurement System
Accurate Hemt Model Extraction And Validation In Class A And B Bias Points Using A Full Two-Port Large Signal On-Wafer Measurement System
Accurate Hemt Model Extraction And Validation In Class A And B Bias Points Using A Full Two-Port Large Signal On-Wafer Measurement System
Simplified Nonquasi-Static Fet Modelling Approach Experimentally Validated Up To 118.5 Ghz
Accurate Hemt Model Extraction And Validation In Class A And B Bias Points Using A Full Two-Port Large Signal On-Wafer Measurement System
Simplified Nonquasi-Static Fet Modelling Approach Experimentally Validated Up To 118.5 Ghz
Enhancing Noise Robustness Of Automatic Parkinson's Disease Detection In Diadochokinesis Tests Using Multicondition Training
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