Adaptive algorithms and stochastic approximations
Adaptive algorithms and stochastic approximations
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
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
Strict identifiability of multiple FIR channels driven by anunknown arbitrary sequence
IEEE Transactions on Signal Processing
Adaptive blind channel estimation by least squares smoothing
IEEE Transactions on Signal Processing
Convergence of stochastic-approximation-based algorithms for blind channel identification
IEEE Transactions on Information Theory
Blind channel identification based on second-order statistics: a frequency-domain approach
IEEE Transactions on Information Theory
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A stochastic approximation algorithm for estimating multichannel coefficients is proposed, and the estimate is proved to converge to the true parameters a.s. up-to a constant scaling factor. The estimate is updated after receiving each new observation, so the output data need not be collected in advance. The input signal is allowed to be dependent and the observation is allowed to be corrupted by noise, but no noise statistics are used in the estimation algorithm.