Matrix analysis
Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Recent developments in blind channel equalization: from cyclostationarity to subspaces
Signal Processing - Special issue on subspace methods, part I: array signal processing and subspace computations
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Adaptive eigenvalue decomposition algorithm for real time acoustic source localization system
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Data-recursive algorithms for blind channel identification inoversampled communication systems
IEEE Transactions on Signal Processing
A least-squares approach to blind channel identification
IEEE Transactions on Signal Processing
Optimization algorithms exploiting unitary constraints
IEEE Transactions on Signal Processing
Fast maximum likelihood for blind identification of multiple FIRchannels
IEEE Transactions on Signal Processing
Adaptive blind channel estimation by least squares smoothing
IEEE Transactions on Signal Processing
Blind multichannel equalization using a novel subspace method
IEEE Transactions on Signal Processing
On gradient adaptation with unit-norm constraints
IEEE Transactions on Signal Processing
Prediction error method for second-order blind identification
IEEE Transactions on Signal Processing
Convergence of stochastic-approximation-based algorithms for blind channel identification
IEEE Transactions on Information Theory
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The multichannel blind identification problem can be formulated as minimizing a cost function based on the cross-relations among different sub-channels, subject to a unit-norm constraint. In this correspondence, this constraint optimization problem is reformulated as an unconstrained one on the Stiefel manifold. Some previously proposed algorithms are also shown to be special cases of this algorithm framework. The convergence and low steady-state misalignment of the proposed algorithms are verified by illustrative computer simulations.