Por favor, use este identificador para citar o enlazar este ítem: http://repositorio.ufc.br/handle/riufc/4167
Tipo: Artigo de Evento
Título : Polynomial expansion of the probability density function about gaussian mixtures
Autor : Cavalcante, Charles Casimiro
Mota, João César Moura
Romano, João Marcos Travassos
Palabras clave : Teleinformática
Fecha de publicación : 2004
Editorial : Workshop on Machine Learning for Signal Processing
Citación : CAVALCANTE, C. C. ; MOTA, J. C. M. ; ROMANO, J. M. T. Polynomial expansion of the probability density function about gaussian mixtures. In: WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 14., 2004, São Luiz. Anais... São Luiz: IEEE, 2004. p. 163-172
Abstract: A polynomial expansion to probability density function (pdf) approximation about Gaussian mixture densities is proposed in this paper. Using known polynomial series expansions we apply the Pareen estimator to derive an orthonormal basis that is able to represent the characteristics of probability distributions that are not concentrated in the vicinity of the mean point such as the Gaussian pdf. The blind source separation problem is used to illustrate the applicability of the proposal in practical analysis of the dynamics of the recovered data pdf estimation. Simulations are carried out to illustrate the analysis.
URI : http://www.repositorio.ufc.br/handle/riufc/4167
Aparece en las colecciones: DETE - Trabalhos apresentados em eventos

Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
2004_eve_cccavalcante.pdf289,48 kBAdobe PDFVisualizar/Abrir


Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.