Fast adaptive blind MMSE equalizer for multichannel FIR systems
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Communications
On MMSE methods for blind identification of OFDM-based SIMO systems
WOCN'09 Proceedings of the Sixth international conference on Wireless and Optical Communications Networks
MUSIC-like DOA estimation without estimating the number of sources
IEEE Transactions on Signal Processing
A constrained optimization approach for an adaptive generalized subspace tracking algorithm
Computers and Electrical Engineering
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This paper describes two new algorithms for tracking the subspace spanned by the principal eigenvectors of the correlation matrix associated with time-domain (i.e., time series) data. The algorithms track the d principal N-dimensional eigenvectors of the data covariance matrix with a complexity of O(Nd2), yet they have performance comparable with algorithms having O(N2d) complexity. The computation reduction is achieved by exploiting the shift-invariance property of temporal data covariance matrices. Experiments are used to compare our algorithms with other well-known approaches of similar and/or lower complexity. Our new algorithms are shown to outperform the subset of the general approaches having the same complexity. The new algorithms are useful for applications such as subspace-based speech enhancement and low-rank adaptive filtering.