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36 642 (0,748s)

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On Computation of Approximate Joint Block-Diagonalization Using Ordinary AJD

Approximate joint block diagonalization (AJBD) of a set of matrices has applications in blind source separation, e.g., when the signal mixtures contain mutually is that certain ordinary approximate joint <...

BB - Aplikovaná statistika, operační výzkum

  • 2012
  • D
  • Link
Result

A Fast Approximate Joint Diagonalization Algorithm Using a Criterion with a Block Diagonal Weight Matrix

We propose a new algorithm for Approximate Joint Diagonalization (AJD) with two main advantages over existing state-of-the-art algorithms: Improved overall running is based on approximate Gauss iterations for succe...

BB - Aplikovaná statistika, operační výzkum

  • 2008
  • D
Result

Two-sided diagonalization of order-three tensors

This paper presents algorithms for two-sided diagonalization of order-three tensors. It is another expression for joint nonsymmetric approximate diagonalization of a set of square matrices, say T_1, . . ., T_M: We ...

BB - Aplikovaná statistika, operační výzkum

  • 2015
  • D
  • Link
Result

Algorithms for nonorthogonal approximate joint block-diagonalization

Approximate joint block diagonalization (AJBD) of a set of matrices has applications in blind source separation, e.g., when the signal mixtures contain mutually independent subspaces of dimension higher than one. In this pa...

BB - Aplikovaná statistika, operační výzkum

  • 2012
  • D
Result

Diagonal approximations by martingales

In the paper, we study and compare several types of approximations of stationary processes by martingales.

BB - Aplikovaná statistika, operační výzkum

  • 2010
  • Jx
Result

Fast Approximate Joint Diagonalization Incorporating Weight Matrices

We propose a new low complexity Approximate Joint Diagonalization (AJD) algorithm, which incorporates nontrivial block-diagonal weight matrices into a Weighted Least-Squares (WLS) AJD criterion. We show how the new...

BB - Aplikovaná statistika, operační výzkum

  • 2009
  • Jx
Result

Non-orthogonal tensor diagonalization

Tensor diagonalization means transforming a given tensor to an exactly or nearly diagonal form through multiplying the tensor by non-orthogonal invertible matrices along selected dimensions ofnthe tensor. It has a link to an app...

Statistics and probability

  • 2017
  • Jimp
  • Link
Result

Extension of the semi-algebraic framework for approximate CP decompositions via non-symmetric simultaneous matrix diagonalization

present an extension of the SECSI (SEmi-algebraic framework for approximate CP decomposition via SImultaneous matrix diagonalization) that is based on new non-symmetric SMDs (Simultaneous Matrix Diagonalizations).nMoreover...

BB - Aplikovaná statistika, operační výzkum

  • 2016
  • D
  • Link
Result

Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization

which can be recovered through the tensor diagonalization. The tensor diagonalization means multiplying tensors by several matrices along its modes so that the outcome is approximately diagonal or block-diagon...

Statistics and probability

  • 2017
  • D
  • Link
Result

In search of convexity: Diagonals and numerical ranges

We show that the set of all possible constant diagonals of a bounded Hilbert space operator is always convex. This, in particular, answers an open question of Bourin (2003). Moreover, we show that the joint numerical range of a comm...

Pure mathematics

  • 2021
  • Jimp
  • Link
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