Petr Tichavsky
Petr Tichavsky
Institute of Information Theory and Automation
Vahvistettu sähköpostiosoite verkkotunnuksessa
Posterior Cramér-Rao bounds for discrete-time nonlinear filtering
P Tichavsky, CH Muravchik, A Nehorai
IEEE Transactions on signal processing 46 (5), 1386-1396, 1998
Efficient variant of algorithm FastICA for independent component analysis attaining the Cramér-Rao lower bound
Z Koldovsky, P Tichavsky, E Oja
IEEE Transactions on neural networks 17 (5), 1265-1277, 2006
Fast approximate joint diagonalization incorporating weight matrices
P Tichavsky, A Yeredor
IEEE Transactions on Signal Processing 57 (3), 878-891, 2008
Performance analysis of the FastICA algorithm and Crame/spl acute/r-rao bounds for linear independent component analysis
P Tichavsky, Z Koldovsky, E Oja
IEEE transactions on Signal Processing 54 (4), 1189-1203, 2006
Near-field/far-field azimuth and elevation angle estimation using a single vector hydrophone
P Tichavsky, KT Wong, MD Zoltowski
IEEE Transactions on Signal Processing 49 (11), 2498-2510, 2001
Fast alternating LS algorithms for high order CANDECOMP/PARAFAC tensor factorizations
AH Phan, P Tichavský, A Cichocki
IEEE Transactions on Signal Processing 61 (19), 4834-4846, 2013
Filtering, predictive, and smoothing Cramér–Rao bounds for discrete-time nonlinear dynamic systems
M Šimandl, J Královec, P Tichavský
Automatica 37 (11), 1703-1716, 2001
Joint matrices decompositions and blind source separation: A survey of methods, identification, and applications
G Chabriel, M Kleinsteuber, E Moreau, H Shen, P Tichavsky, A Yeredor
IEEE Signal Processing Magazine 31 (3), 34-43, 2014
Stable low-rank tensor decomposition for compression of convolutional neural network
AH Phan, K Sobolev, K Sozykin, D Ermilov, J Gusak, P Tichavský, ...
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Low complexity damped Gauss--Newton algorithms for CANDECOMP/PARAFAC
AH Phan, P Tichavsky, A Cichocki
SIAM Journal on Matrix Analysis and Applications 34 (1), 126-147, 2013
Comparative study of four adaptive frequency trackers
P Tichavsky, A Nehorai
IEEE Transactions on Signal Processing 45 (6), 1473-1484, 1997
Two algorithms for adaptive retrieval of slowly time-varying multiple cisoids in noise
P Tichavsky, P Handel
IEEE Transactions on Signal Processing 43 (5), 1116-1127, 1995
Optimal pairing of signal components separated by blind techniques
P Tichavsky, Z Koldovsky
IEEE Signal Processing Letters 11 (2), 119-122, 2004
Weight adjusted tensor method for blind separation of underdetermined mixtures of nonstationary sources
P Tichavsky, Z Koldovsky
IEEE Transactions on Signal Processing 59 (3), 1037-1047, 2010
Time-domain blind audio source separation using advanced component clustering and reconstruction
Z Koldovsky, P Tichavsky
2008 Hands-Free Speech Communication and Microphone Arrays, 216-219, 2008
Gradient algorithms for complex non-gaussian independent component/vector extraction, question of convergence
Z Koldovský, P Tichavský
IEEE Transactions on Signal Processing 67 (4), 1050-1064, 2018
Cross-product algorithms for source tracking using an EM vector sensor
A Nehorai, P Tichavsky
IEEE Transactions on Signal Processing 47 (10), 2863-2867, 1999
Time-domain blind separation of audio sources on the basis of a complete ICA decomposition of an observation space
Z Koldovsky, P Tichavský
IEEE transactions on audio, speech, and language processing 19 (2), 406-416, 2010
A hybrid technique for blind separation of non-Gaussian and time-correlated sources using a multicomponent approach
P Tichavsky, Z Koldovsky, A Yeredor, G Gómez-Herrero, E Doron
IEEE Transactions on Neural Networks 19 (3), 421-430, 2008
CANDECOMP/PARAFAC decomposition of high-order tensors through tensor reshaping
AH Phan, P Tichavský, A Cichocki
IEEE Transactions on Signal Processing 61 (19), 4847-4860, 2013
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