The Frisch scheme in dynamic system identification
Automatica (Journal of IFAC) - Identification and system parameter estimation
On performance of cross-relation method for blind-channel identification
Signal Processing
EVAM: an eigenvector-based algorithm for multichannel blinddeconvolution of input colored signals
IEEE Transactions on Signal Processing
Adaptive solution for blind identification/equalization usingdeterministic maximum likelihood
IEEE Transactions on Signal Processing
A least-squares approach to blind channel identification
IEEE Transactions on Signal Processing
Subspace methods for the blind identification of multichannel FIRfilters
IEEE Transactions on Signal Processing
Fast maximum likelihood for blind identification of multiple FIRchannels
IEEE Transactions on Signal Processing
Strict identifiability of multiple FIR channels driven by anunknown arbitrary sequence
IEEE Transactions on Signal Processing
On subspace methods for blind identification of single-inputmultiple-output FIR systems
IEEE Transactions on Signal Processing
Prediction error method for second-order blind identification
IEEE Transactions on Signal Processing
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Blind identification is a very significant problem in many contexts where only the output of transmission channels can be observed. The solutions that can be found in the literature are limited to the case of equal amounts of additive noise on the observations. This paper proposes new identification procedures that can be applied to the case of two FIR channels affected by unknown and unbalanced amounts of additive noise. The identified models are then used for the minimal variance deconvolution of the unknown input signal. Several Monte Carlo simulations also confirm the good performance of these procedures in severe SNR conditions.