Linear and nonlinear smoothing algorithms for widely factorizable signals

Authors:
Rosa MaríA FernáNdez-Alcalá;JesúS Navarro-Moreno;Juan Carlos Ruiz-Molina;Juan Antonio Espinosa-Pulido
Affiliations:
University of Jaén, Department of Statistics and Operations Research, Campus Las Lagunillas, 23071 Jaén, Spain and IES Llano de la Viña de Villargordo, C/ Ramiro Aguilera s/n, 23630 ...;University of Jaén, Department of Statistics and Operations Research, Campus Las Lagunillas, 23071 Jaén, Spain and IES Llano de la Viña de Villargordo, C/ Ramiro Aguilera s/n, 23630 ...;University of Jaén, Department of Statistics and Operations Research, Campus Las Lagunillas, 23071 Jaén, Spain and IES Llano de la Viña de Villargordo, C/ Ramiro Aguilera s/n, 23630 ...;University of Jaén, Department of Statistics and Operations Research, Campus Las Lagunillas, 23071 Jaén, Spain and IES Llano de la Viña de Villargordo, C/ Ramiro Aguilera s/n, 23630 ...
Venue:
Signal Processing
Year:
2013

Citing 9
Cited 0

An introduction to signal detection and estimation (2nd ed.)

An introduction to signal detection and estimation (2nd ed.)
Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models

Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
Widely linear estimation algorithms for second-order stationary signals

IEEE Transactions on Signal Processing
An augmented affine projection algorithm for the filtering of noncircular complex signals

Signal Processing
ARMA Prediction of Widely Linear Systems by Using the Innovations Algorithm

IEEE Transactions on Signal Processing - Part II
Second-order statistics of complex signals

IEEE Transactions on Signal Processing
Widely linear estimation with complex data

IEEE Transactions on Signal Processing
Smoothing for doubly stochastic Poisson processes

IEEE Transactions on Information Theory
Widely linear prediction for transfer function models based on the infinite past

Computational Statistics & Data Analysis

Quantified Score

Hi-index	0.08

Visualization

Abstract

The fixed-point smoothing estimation problem is analyzed for a class of improper complex-valued signals, called widely factorizable, characterized because the correlation of the augmented vector formed by the signal and its conjugate is a factorizable kernel. For this type of signal, widely linear processing is the most suitable approach considering the complete information of the augmented correlation function. Then, from only the knowledge of the second order properties of the augmented vectors involved, linear and nonlinear smoothing algorithms are provided without the necessity of postulating a state-space model. Moreover, in the linear case, recursive formulas for computing the fixed-point smoothing estimation error are proposed.