Denoising using local projective subspace methods
Neurocomputing
Multiuser channel estimation from higher-order statistical matrix pencil
EURASIP Journal on Applied Signal Processing
The generalized eigendecomposition approach to the blind source separation problem
Digital Signal Processing
Blind estimation of signal in periodic long-code DSSS communications
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
An iterative equalization method for nonirreducible MIMO FIR channels
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
| Hi-index | 35.68 |
A new two-stage algorithm is proposed for the deconvolution of multi-input multi-output (MIMO) systems with colored input signals. While many blind deconvolution algorithms in the literature utilize high order statistics of the output signal for white input signals, the additional information contained in colored input signals allows the design of second-order statistical algorithms. In fact, practical signal sources such as speech signals do have distinct, nonstationary, colored power spectral densities. We present a two-stage signal separation approach in which the first step utilizes a matrix pencil between output auto-correlation matrices at different delays, whereas the second stage adopts a subspace method to identify and deconvolve MIMO systems