Time series: theory and methods
Time series: theory and methods
Estimating the parameters of complex-valued exponential signals
Computational Statistics & Data Analysis
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Complex-valued ICA based on a pair of generalized covariance matrices
Computational Statistics & Data Analysis
Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
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
Simulation of Improper Complex-Valued Sequences
IEEE Transactions on Signal Processing
Widely linear estimation with complex data
IEEE Transactions on Signal Processing
Widely linear reception strategies for layered space-time wireless communications
IEEE Transactions on Signal Processing - Part I
Detection and estimation of improper complex random signals
IEEE Transactions on Information Theory
Editorial: The third special issue on Statistical Signal Extraction and Filtering
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
The problem of widely linear (WL) prediction for both WL ARMA models and WL transfer function models on the basis of infinite past information is studied. A recursive algorithm to obtain a suboptimum predictor for WL ARMA systems is first given. Then this algorithm is used to develop another recursive algorithm which performs WL prediction for transfer function models. The suggested solutions become an alternative to the WL prediction based on a finite number of observations provided the size of the time series is sufficiently large.