Documentos de Mun̈oz-Marí J. | REDI

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Filtros aplicados

Objetivos de Desarrollo Sostenible: "ODS 4: Educación de calidad"

Subtipo de publicación

Publisher

Digital Signal Processing: A Review Journal(1)

IEEE Signal Processing Letters(1)

IEEE Transactions on Neural Networks(1)

IEEE Transactions on Neural Networks and Learning Systems(1)

Neurocomputing(1)

Área temáticas

Ciencias de la computación(3)

Métodos informáticos especiales(1)

Programación informática, programas, datos, seguridad(1)

Área de conocimiento

Aprendizaje automático(3)

Optimización matemática(3)

Procesamiento de señales(1)

Objetivos de Desarrollo Sostenible

ODS 9: Industria, innovación e infraestructura(5)

ODS 17: Alianzas para lograr los objetivos(4)

ODS 3: Salud y bienestar(1)

Año de Publicación

Origen

Palabras Claves

Composite kernels(1)

Deconvolution(1)

Digital processing(1)

A unified SVM framework for signal estimation

Abstract: This paper presents a review in the form of a unified framework for tackling estimation problems in

Palabras claves:

Deconvolution, Digital processing, Filtering, Kernel method, Signal estimation, Spectral estimation, Support vector, system identification

Camps-Valls G., Jose Luis Rojo-Álvarez, Martinez-Ramon M., Mun̈oz-Marí J.

Explicit recursive and adaptive filtering in reproducing kernel hilbert spaces

Abstract: This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces.

Palabras claves:

Adaptive, autoregressive and moving-average, filter, kernel methods, recursive

Camps-Valls G., Jose Luis Rojo-Álvarez, Martinez-Ramon M., Mun̈oz-Marí J., Tuia D.

Learning non-linear time-scales with kernel γ-filters

Abstract: A family of kernel methods, based on the γ-filter structure, is presented for non-linear system iden

Palabras claves:

Gamma filter, Kernel, Non-linear system identification, Support Vector Machine

Camps-Valls G., Jose Luis Rojo-Álvarez, Martinez-Ramon M., Mun̈oz-Marí J., Requena-Carrión J.

Nonlinear system identification with composite relevance vector machines

Abstract: Nonlinear system identification based on relevance vector machines (RVMs) has been traditionally add

Palabras claves:

Composite kernels, Nonlinear system identification, Relevance vector machine (RVM)

Camps-Valls G., Jose Luis Rojo-Álvarez, Martinez-Ramon M., Mun̈oz-Marí J.

Support vector machines for nonlinear Kernel ARMA system identification

Abstract: Nonlinear system identification based on support vector machines (SVM) has been usually addressed by

Palabras claves:

Camps-Valls G., Figueiras-Vidal A.R., Jose Luis Rojo-Álvarez, Martinez-Ramon M., Mun̈oz-Marí J., Navia-Vázquez A., Soria-Olivas E.