Zobrazeno 1 - 10
of 246
pro vyhledávání: '"Brie David"'
This article characterizes the rank-one factorization of auto-correlation matrix polynomials. We establish a sufficient and necessary uniqueness condition for uniqueness of the factorization based on the greatest common divisor (GCD) of multiple poly
Externí odkaz:
http://arxiv.org/abs/2308.15106
Autor:
Borsoi, Ricardo Augusto, Lehmann, Isabell, Akhonda, Mohammad Abu Baker Siddique, Calhoun, Vince, Usevich, Konstantin, Brie, David, Adali, Tülay
Discovering components that are shared in multiple datasets, next to dataset-specific features, has great potential for studying the relationships between different subjects or tasks in functional Magnetic Resonance Imaging (fMRI) data. Coupled matri
Externí odkaz:
http://arxiv.org/abs/2211.14253
This work introduces a novel Fourier phase retrieval model, called polarimetric phase retrieval that enables a systematic use of polarization information in Fourier phase retrieval problems. We provide a complete characterization of uniqueness proper
Externí odkaz:
http://arxiv.org/abs/2206.12868
Activation functions (AFs) are an important part of the design of neural networks (NNs), and their choice plays a predominant role in the performance of a NN. In this work, we are particularly interested in the estimation of flexible activation funct
Externí odkaz:
http://arxiv.org/abs/2106.13542
This paper introduces a general framework for solving constrained convex quaternion optimization problems in the quaternion domain. To soundly derive these new results, the proposed approach leverages the recently developed generalized $\mathbb{HR}$-
Externí odkaz:
http://arxiv.org/abs/2102.02763
Autor:
Borsoi, Ricardo Augusto, Prévost, Clémence, Usevich, Konstantin, Brie, David, Bermudez, José Carlos Moreira, Richard, Cédric
Coupled tensor approximation has recently emerged as a promising approach for the fusion of hyperspectral and multispectral images, reconciling state of the art performance with strong theoretical guarantees. However, tensor-based approaches previous
Externí odkaz:
http://arxiv.org/abs/2006.16968
This article introduces quaternion non-negative matrix factorization (QNMF), which generalizes the usual non-negative matrix factorization (NMF) to the case of polarized signals. Polarization information is represented by Stokes parameters, a set of
Externí odkaz:
http://arxiv.org/abs/1903.10593
We propose a novel approach for hyperspectral super-resolution, that is based on low-rank tensor approximation for a coupled low-rank multilinear (Tucker) model. We show that the correct recovery holds for a wide range of multilinear ranks. For coupl
Externí odkaz:
http://arxiv.org/abs/1811.11091
Publikováno v:
In Signal Processing September 2022 198
Zero-attracting least-mean-square (ZA-LMS) algorithm has been widely used for online sparse system identification. It combines the LMS framework and $\ell_1$-norm regularization to promote sparsity, and relies on subgradient iterations. Despite the s
Externí odkaz:
http://arxiv.org/abs/1608.07046