نتایج جستجو برای: tensor decomposition
تعداد نتایج: 139824 فیلتر نتایج به سال:
INTRODUCTION The diffusion tensor is a 3x3 positive definite matrix and, therefore, possesses several distinct matrix decompositions, e.g. the Cholesky, and the Eigenvalue decompositions. To date, the Eigenvalue decomposition has been used only in computing tensor-derived quantities [1-4] but not as a parametrization (or equivalently, a representation) in DTI error propagation [5]. Treating a m...
Digital Watermarking is a technology used for the copyright protection and authentication of digital application. The commercial activity on the internet and media require protection to enhance security. We proposed a new invisible non-blind video watermarking in Quick Response (QR) code technique. In one video frame we embed text message into QR Code image and further embed logo into QR-Code i...
In this paper, we propose a novel algorithm for underdetermined blind identification problems in blind signal separation. The proposed algorithm is based on the charrelation matrix of observations. The charrelation matrix can not only be considered as a generalized covariance matrix, but also incorporates higher-order information. It is significant for blind separation problem based on statisti...
To every regular category $\mathcal{A}$ equipped with a degree function $\delta$ one can attach pseudo-abelian tensor $\mathcal{T}(\mathcal{A},\delta)$. We show that the generating objects of $\mathcal{T}$ decompose canonically as direct sum. In this paper we calculate morphisms, compositions morphisms and products summands. As special case recover original construction Deligne's $\operatorname...
The so-called block-term decomposition (BTD) tensor model, especially in its rank-(Lr,Lr,1) version, has been recently receiving increasing attention due to enhanced ability represent systems and signals that are composed of block components rank higher than one, a scenario encountered numerous diverse applications. Its uniqueness approximation have thus thoroughly studied. challenging problem ...
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