Tensor-based techniques for the blind separation of DS-CDMA signals
From MaRDI portal
Publication:970676
DOI10.1016/j.sigpro.2005.12.015zbMath1186.94413OpenAlexW2082658029MaRDI QIDQ970676
Joséphine Castaing, Lieven De Lathauwer
Publication date: 19 May 2010
Published in: Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.sigpro.2005.12.015
higher-order tensorsignal separationcode division multiple accessmulti-linear algebrablind techniqueconstant modulus
Related Items
Finding the limit of diverging components in three-way Candecomp/Parafac -- a demonstration of its practical merits ⋮ Rank-1 Tensor Properties with Applications to a Class of Tensor Optimization Problems ⋮ The stratification by rank for homogeneous polynomials with border rank 5 which essentially depend on five variables ⋮ Symmetric tensor decomposition ⋮ Computing symmetric rank for symmetric tensors ⋮ Tensor decomposition and homotopy continuation ⋮ Nearest-neighbor interaction systems in the tensor-train format ⋮ Real and complex rank for real symmetric tensors with low ranks ⋮ Higher secant varieties of \(\mathbb P^n \times \mathbb P^n\) embedded in bi-degree \((1,d)\) ⋮ Partitioned treatment of uncertainty in coupled domain problems: a separated representation approach ⋮ Non-intrusive low-rank separated approximation of high-dimensional stochastic models ⋮ Alternating direction method of multipliers for generalized low-rank tensor recovery ⋮ Total variation based tensor decomposition for multi‐dimensional data with time dimension ⋮ The tensor rank problem over the quaternions ⋮ Polynomial meta-models with canonical low-rank approximations: numerical insights and comparison to sparse polynomial chaos expansions ⋮ Subtracting a best rank-1 approximation may increase tensor rank ⋮ Exact line and plane search for tensor optimization ⋮ Blind equalization of nonlinear channels using a tensor decomposition with code/space/time diversities ⋮ Differential-geometric Newton method for the best rank-\((R _{1}, R _{2}, R _{3})\) approximation of tensors ⋮ Numerical Computation for Orthogonal Low-Rank Approximation of Tensors ⋮ On Koopman mode decomposition and tensor component analysis ⋮ The Hitchhiker guide to: secant varieties and tensor decomposition