A stochastic sparse representation: \(n\)-best approximation to random signals and computation

DOI10.1016/j.acha.2021.05.003zbMath1471.94012OpenAlexW3161805984MaRDI QIDQ1979920

Wei Qu, Tao Qian, Guan Tie Deng

Publication date: 3 September 2021

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.acha.2021.05.003

zbMATH Keywords

image processingreproducing kernelsignal analysisrandom signalstochastic Hardy spacestochastic Hilbert space

Mathematics Subject Classification ID

Stationary stochastic processes (60G10) Signal detection and filtering (aspects of stochastic processes) (60G35) Best approximation, Chebyshev systems (41A50) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) General theory of stochastic processes (60G07) Approximation by other special function classes (41A30) Series expansions of functions of one complex variable (30B99)

Related Items (3)

\(n\)-best kernel approximation in reproducing kernel Hilbert spaces ⋮ Adaptive Fourier decomposition‐type sparse representations versus the Karhunen–Loève expansion for decomposing stochastic processes ⋮ Uncertainty principles for random signals

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