We study the behavior of the subspace method in the case where the order of the transfer function is overestimated.
Abstract—In this contribution, the problem of blind identifi- cation of p-inputs/q-outputs FIR transfer functions is addressed. Existing subspace ...
This algorithm operates directly on the data domain and therefore avoids the problems associ- ated with other algorithms which use the statistical informa- tion ...
Article Dans Une Revue IEEE Transactions on Information Theory Année : 1997. A subspace algorithm for certain blind identification problems.
A new method is proposed for the blind subspace-based iden- tification of the coefficients of time-varying (TV) single-input.
[PDF] Error correcting least-squares Subspace algorithm for blind ...
sig.umd.edu › Sampath_SP_200109
Abstract. A subspace based blind channel identification algorithm using only the fact that the received signal can be oversampled is proposed.
A covariance-driven subspace identification method is presented to identify weakly excited modes. In this method, the traditional block Hankel matrix is ...
Like subspace techniques founded in sensor array processing, the KR subspace formulation enables us to decompose the BID problem into a per-source decoupled BID ...
In this paper, we study the deterministic blind identification of multiple channel state-space models having a common unknown input using measured output ...
This paper presents a review of channel identification methods that are applicable in this context, with a strong emphasis on second-order subspace-based and ...