Blind ZF equalization with controlled delay robust to order over estimation
Signal Processing - From signal processing theory to implementation
Blind linear channel estimation using genetic algorithm and SIMO model
Signal Processing
A blind MIMO channel estimation method robust to order overestimation
Signal Processing - Special issue on independent components analysis and beyond
Global convergence of a blind multichannel identification algorithm
Signal Processing
Blind identification and equalization of two-channel FIR systems in unbalanced noise environments
Signal Processing - Content-based image and video retrieval
Blind estimation of MIMO channels with an upper bound for channel orders
Signal Processing
Self-tuning blind identification and equalization of IIR channels
EURASIP Journal on Applied Signal Processing
Dereverberation by using time-variant nature of speech production system
EURASIP Journal on Advances in Signal Processing
EURASIP Journal on Advances in Signal Processing
Fast communication: Blind SIMO channel identification using FFT/IFFT
Signal Processing
Blind identification of MISO-FIR channels
Signal Processing
Blind MIMO-AR system identification and source separation with finite-alphabet
IEEE Transactions on Signal Processing
Blind adaptive equalization of MIMO systems: new recursive algorithms and convergence analysis
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Speech dereverberation based on variance-normalized delayed linear prediction
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
Blind system identification using precise and quantized observations
Automatica (Journal of IFAC)
Hi-index | 35.69 |
Blind channel identification methods based on the oversampled channel output are a problem of current theoretical and practical interest. In this paper, we introduce a second-order blind identification technique based on a linear prediction approach. In contrast to eigenstructure-based methods, it will be shown that the linear prediction error method is “robust” to order overdetermination. An asymptotic performance analysis of the proposed estimation method is carried out, consistency and asymptotic normality of the estimates is established. A closed-form expression for the asymptotic covariance of the estimates is given. Numerical simulations and investigations are finally presented to demonstrate the potential and the “robustness” of the proposed method