A Greedy Algorithm To Extract Sparsity Degree For L1/L0-Equivalence In A Deterministic Context
, 2012 Publication in the conference proceedings of EUSIPCO, Bucharest, Romania ...
Pustelnik, Nelly +4 more
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On the Equivalence of Youla, System-level and Input-output Parameterizations
, 2019 A convex parameterization of internally stabilizing controllers is fundamental for many controller synthesis procedures. The celebrated Youla parameterization relies on a doubly-coprime factorization of the system, while the recent system-level and input-
Furieri, Luca +4 more
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Realizability and Internal Model Control on Networks
, 2019 It is proved that network realizability of controllers can be enforced without conservatism using convex constraints on the closed loop transfer function.
boyd, wang
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RSP-Based Analysis for Sparsest and Least $\ell_1$-Norm Solutions to Underdetermined Linear Systems
, 2013 Recently, the worse-case analysis, probabilistic analysis and empirical justification have been employed to address the fundamental question: When does $\ell_1$-minimization find the sparsest solution to an underdetermined linear system? In this paper, a
Zhao, Yunbin
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Regularized Spherical Polar Fourier Diffusion MRI with Optimal Dictionary Learning
, 2013 Compressed Sensing (CS) takes advantage of signal sparsity or compressibility and allows superb signal reconstruction from relatively few measurements. Based on CS theory, a suitable dictionary for sparse representation of the signal is required.
Cheng, Jian +4 more
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IEEE AccessThis study introduces a robust approach for denoising pressure signals by integrating Improved Complete Ensemble Empirical Mode Decomposition (ICEEMDAN), Continuous Mean Square Error (CMSE) analysis, optimal wavelet selection, and wavelet thresholding ...
Van-Trung Nguyen, Minh-Tien Nguyen
doaj +1 more source
Sparsity Equivalence of Anisotropic Decompositions
, 2011 Anisotropic decompositions using representation systems such as curvelets, contourlet, or shearlets have recently attracted significantly increased attention due to the fact that they were shown to provide optimally sparse approximations of functions exhibiting singularities on lower dimensional embedded manifolds.
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Graphical modeling of stochastic processes driven by correlated errors
, 2020 We study a class of graphs that represent local independence structures in stochastic processes allowing for correlated error processes. Several graphs may encode the same local independencies and we characterize such equivalence classes of graphs.
Hansen, Niels Richard +1 more
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Network Flow Algorithms for Structured Sparsity [PDF]
, 2010 We consider a class of learning problems that involve a structured sparsity-inducing norm defined as the sum of $\ell_\infty$-norms over groups of variables. Whereas a lot of effort has been put in developing fast optimization methods when the groups are
Bach, Francis +3 more
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On the Equivalence Between a Minimal Codomain Cardinality Riesz Basis Construction, a System of Hadamard–Sylvester Operators, and a Class of Sparse, Binary Optimization Problems [PDF]
, 2014 Piecewise, low-order polynomial, Riesz basis families are constructed such that they share the same coefficient functionals of smoother, orthonormal bases in a localized indexing subset.
Nelson, JDB
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