Blind separation of convolutive mixtures by decorrelation
Signal Processing
A blind source separation framework for detecting CPM sources mixed by a convolutive MIMO filter
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Blind identification of convolutive MIMO systems with 3 sources and 2 sensors
EURASIP Journal on Applied Signal Processing
Multiuser channel estimation from higher-order statistical matrix pencil
EURASIP Journal on Applied Signal Processing
Blind separation of nonstationary sources based on spatial time-frequency distributions
EURASIP Journal on Applied Signal Processing
Blind paraunitary equalization
Signal Processing
Blind paraunitary equalization
Signal Processing
An approach to surface EMG decomposition based on higher-order cumulants
Computer Methods and Programs in Biomedicine
A new second-order method for blind signal separation from dynamic mixtures
Computers and Electrical Engineering
A novel algorithm to improve the blind receiver for convolutive MIMO systems
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Nonorthogonal approximate joint diagonalization with well-conditioned diagonalizers
IEEE Transactions on Neural Networks
Blind Deconvolution of Multi-Input Single-Output Systems Using the Distribution of Point Distances
Journal of Signal Processing Systems
Hi-index | 35.68 |
We present a novel frequency-domain framework for the identification of a multiple-input multiple-output (MIMO) system driven by white, mutually independent, unobservable inputs. The system frequency response is obtained based on singular value decomposition (SVD) of a matrix constructed based on the power-spectrum and slices of polyspectra of the system output. By appropriately selecting the polyspectra slices, we can create a set of such matrices, each of which could independently yield the solution, of they could all be combined in a joint diagonalization scheme to yield a solution with improved statistical performance. The freedom to select the polyspectra slices allows us to bypass the frequency-dependent permutation ambiguity that is usually associated with frequency domain SVD, while at the same time allows us compute and cancel the phase ambiguity. An asymptotic consistency analysis of the system magnitude response estimate is performed