Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain

Consider us the problem of time-varying parameter estimation. The most immediate and simple idea is to include a discounting procedure in an estimation algorithm i.e., a procedure for discarding (forgetting) old information. The most common way to do is to introduce an exponential forgetting factor...

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Detalles Bibliográficos
Autores principales: Jesús Medel Juárez, José de, Guevara López, Pedro, Flores Rueda, Alberto
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2004
Materias:
Ciencias Informáticas
Filtering
estimation
signal processing.
Simulation
Parallel processing
Distributed
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22497
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22497
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Filtering
estimation
signal processing.
Simulation
Parallel processing
Distributed
spellingShingle Ciencias Informáticas
Filtering
estimation
signal processing.
Simulation
Parallel processing
Distributed
Jesús Medel Juárez, José de
Guevara López, Pedro
Flores Rueda, Alberto
Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
topic_facet Ciencias Informáticas
Filtering
estimation
signal processing.
Simulation
Parallel processing
Distributed
description Consider us the problem of time-varying parameter estimation. The most immediate and simple idea is to include a discounting procedure in an estimation algorithm i.e., a procedure for discarding (forgetting) old information. The most common way to do is to introduce an exponential forgetting factor (FF) into the corresponding estimation procedure (to see: Ljung and Gunnarson (1990)). In this paper, the authors going to describe a good enough estimator considering a system with nonstationary time variant properties with respect to input and output qualities. The techniques used are Instrumental Variable (IV) and Matrix Forgetting Factor (MFF). The results previously obtained by (Poznyak and Medel 1999a, 1999b) were the basis of this paper. The theoretical description illustrates the advantages with respect to others filters below cited.
format Objeto de conferencia
Objeto de conferencia
author Jesús Medel Juárez, José de
Guevara López, Pedro
Flores Rueda, Alberto
author_facet Jesús Medel Juárez, José de
Guevara López, Pedro
Flores Rueda, Alberto
author_sort Jesús Medel Juárez, José de
title Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
title_short Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
title_full Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
title_fullStr Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
title_full_unstemmed Matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
title_sort matrix estimation using matrix forgetting factor and instrumental variable for nonstationary sequences with time variant matrix gain
publishDate 2004
url http://sedici.unlp.edu.ar/handle/10915/22497
work_keys_str_mv AT jesusmedeljuarezjosede matrixestimationusingmatrixforgettingfactorandinstrumentalvariablefornonstationarysequenceswithtimevariantmatrixgain
AT guevaralopezpedro matrixestimationusingmatrixforgettingfactorandinstrumentalvariablefornonstationarysequenceswithtimevariantmatrixgain
AT floresruedaalberto matrixestimationusingmatrixforgettingfactorandinstrumentalvariablefornonstationarysequenceswithtimevariantmatrixgain
bdutipo_str Repositorios
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