J
Jose C. M. Bermudez
Researcher at Universidade Federal de Santa Catarina
Publications - 231
Citations - 4410
Jose C. M. Bermudez is an academic researcher from Universidade Federal de Santa Catarina. The author has contributed to research in topics: Adaptive filter & Monte Carlo method. The author has an hindex of 28, co-authored 226 publications receiving 3672 citations. Previous affiliations of Jose C. M. Bermudez include Federal University of Rio de Janeiro & Universidade Católica de Pelotas.
Papers
More filters
Journal ArticleDOI
Online Prediction of Time Series Data With Kernels
TL;DR: This paper investigates a new model reduction criterion that makes computationally demanding sparsification procedures unnecessary and incorporates the coherence criterion into a new kernel-based affine projection algorithm for time series prediction.
Journal ArticleDOI
Nonlinear Unmixing of Hyperspectral Images: Models and Algorithms
Nicolas Dobigeon,Jean-Yves Tourneret,Cedric Richard,Jose C. M. Bermudez,Stephen McLaughlin,Alfred O. Hero +5 more
TL;DR: In this article, the authors present an overview of recent advances in nonlinear unmixing modeling, for instance, when there are multiscattering effects or intimate interactions, and several significant contributions have been proposed to overcome the limitations inherent in the LMM.
Journal ArticleDOI
Nonlinear unmixing of hyperspectral images: models and algorithms
Nicolas Dobigeon,Jean-Yves Tourneret,Cedric Richard,Jose C. M. Bermudez,Stephen McLaughlin,Alfred O. Hero +5 more
TL;DR: This article presents an overview of recent advances in nonlinear unmixing modeling and proposes several significant contributions to overcome the limitations inherent in the LMM.
Journal ArticleDOI
An Affine Combination of Two LMS Adaptive Filters—Transient Mean-Square Analysis
TL;DR: This paper studies the statistical behavior of an affine combination of the outputs of two least-mean-square adaptive filters that simultaneously adapt using the same white Gaussian inputs to obtain an LMS adaptive filter with fast convergence and small steady-state mean-square deviation (MSD).
Journal ArticleDOI
Mean weight behavior of the filtered-X LMS algorithm
TL;DR: A new stochastic analysis is presented for the filtered-X LMS (FXLMS) algorithm and an analytical model is derived for the mean behavior of the adaptive weights.