Bibliography
Conference Paper (international conference)
Under-Determined Tensor Diagonalization for Decomposition of Difficult Tensors
, ,
: IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) 2017 , p. 263-266
: CAMSAP 2017 - 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, (Curacao, NL, 20171210)
: GA17-00902S, GA ČR
: canonical polyadic decomposition, tensor decomposition, matrix multiplication
: http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0483430.pdf
(eng): This paper deals with the Cramer-Rao Lower Bound (CRLB) for a novel blind source separation method called Independent Component Extraction (ICE). Compared to Independent Component Analysis (ICA), ICE aims to extract only one independent signal from a linear mixture. The target signal is assumed to be non-Gaussian, while the other signals, which are not separated, are modeled as a Gaussian mixture. A CRLBinduced Bound (CRIB) for Interference-to-Signal Ratio (ISR)\nis derived. Numerical simulations compare the CRIB with the performance of an ICA and an ICE algorithm. The results show good agreement between the theory and the empirical results.
: BB
: 10103