Personal
pages of PETR TICHAVSKÝ |

This page offers a free download of matlab/C++
codes developed by Petr Tichavsky and his co-workers that are cited in
his/their publications. We only ask for a registration of any user,
using the codes for educational purposes only, and for properly citing
of the papers/web page.

Exact location of the codes will be send to the interested users by automatically generated e-mail, containing (hopefully) all necessary details.

A feedback on the codes is highly appreciated.

Software for evaluation purposes (for a review process):
tensor diagonalization algorithm for regular tensors TEDIA
and for rank-deficient tensors TEDIA_RD
Exact location of the codes will be send to the interested users by automatically generated e-mail, containing (hopefully) all necessary details.

A feedback on the codes is highly appreciated.

Software for numerical CP decomposition of difficult tensors: (1) constrained Levenberg-Marquardt algorithm (2) script for generating a tensor correspodning to the matrix multiplication (3) code that transformes a given exact-fit solution to a sparse exact fit solution A feedback on the codes is highly appreciated.

The other software is available upon a registration.

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codes.

- Estimating the Mutual Information
- Optimum Pairing
- Approximate Joint Diagonalization Algorithms
- Blind Source Separation (BSS) Algorithms: WASOBI and BGSEP
- Removing Artifacts in (Neonatal) EEG Data
- BARBI - A BSS algorithm based on the signal nonstationarity and the spectral diversity. AR1sep - specialized BSS algorithm for separating underdetermined mixtures of piecewise AR1 sources, published at ICASSP 2016.
- Algorithms COMBI and MULTI-COMBI - BSS algorithms based on combination of the signal non-Gaussianity and the spectral diversity
- Generator of a Generalized Gaussian distributed matrices
- FicaCPLX - A BSS algorithm for separating complex-valued signals based on non-Gaussianity, with optimalized suppression of the additive noise
- Tensor Factorization Algorithms & Application: PALS, PALSE - partitioned ALS algorithms for CP tensor decomposition, see IEEE Signal Processing Letters 2016. UDSEP, blind separation of undetermined mixtures of nonstationary sources

- UWEDGE - Uniformly Weighted Exhaustive Diagonalization with Gauss itErations
- WEDGE - Weighted Exhaustive Diagonalization with Gauss itErations (with user-provided weight matrices)
- BG-WEDGE - it is WEDGE with special choice of the weight matrices that correspond to joint diagonalization of covariance matrices in blind source separation of Block-wise stationary Gaussian signals. It represents a fast alternative to the Pham's algorithm "jadiag".
- UWEDGE_C - Complex version (version for complex-valued matrices and complex-valued mixing) of the algorithm UWEDGE

BGSEP is a BSS algorithm based on the signal nonstationarity This algorithm is used e.g. in the time-domain blind separation of convolutive mixtures by Koldovsky and Tichavsky. Basically, it computes sample covariance matrices of the multichannel signal on a partitioning to non-overlapping intervals of an equal size, and applies an algorithm for approximate joint diagonalization with appropriate weights (BGWEDGE).

A short version was published as

P.Tichavsky, M. Zima, and V. Krajca, ``Automatic removal of sparse artifacts in electroencephalogram", Proc. Biosignals 2011, Rome, Italy, January 26-29, 2011, pp. 530-535.

Coded by Miroslav Zima and Petr Tichavsky, November 2011.

See the paper

P. Tichavsky, A. Yeredor, and Z.Koldovsky, ``A Fast Asymptotically Efficient Algorithm for Blind Separation of a Linear Mixture of Block-Wise Stationary Autoregressive Processes",

AR1sep = algorithm published as
O. Sembera, P. Tichavsky and Z. Koldovsky, "Blind separation of underdetermined
linear mixtures based on source nonstationarity and AR(1) modeling."

A matlab implementation of algorithms COMBI and MULTI-COMBI
that are hybrid of algorithms
of algorithm EFICA and WASOBI, utilizing strong features of both
algorithms
P. Tichavsky, Z. Koldovsky, A. Yeredor, G.
Gomez-Herrero, and E. Doron, ``A Hybrid Technique for Blind Separation
of Non-Gaussian and Time-Correlated Sources Using a Multicomponent Approach",
*IEEE Tr. Neural Networks*, vol. 19, no. 3, pp. 421-430, March 2008.

Algorithm FicaCPLX that is a variant of the algorithm FastICA
for blind separation of complex-valued sources, implementing a new test
of saddle points and an one-unit refinement
for each component. As a reference, please cite Zbynek's and my paper
presented at ICA'07 in London, see Publications.

(2) Constrained Levenberg-Marquardt CP decomposition algorithm, specially suitable for decomposition of tensors representing small matrix multiplications, presented at TDA workshop in Leuven, Belgium, January 2016.

(3) UDSEP is a BSS algorithm aiming to separate mixtures of nonstationary signals where there are more sources than sensors. The algorithm was described in the paper Tichavsky, Z. Koldovsky, "Weight adjusted tensor method for blind separation of underdetermined mixtures of nonstationary sources",