New aspects of Beurling-Lax shift invariant subspaces

DOI10.1016/j.amc.2014.12.147zbMath1338.94021OpenAlexW2085763262MaRDI QIDQ299617

Tao Qian, Li-Hui Tan, Qiu-hui Chen

Publication date: 22 June 2016

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2014.12.147

zbMATH Keywords

backward shift invariant subspaceband preserving problemBedrosian identityforward shift invariant subspace

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Fourier and Fourier-Stieltjes transforms and other transforms of Fourier type (42A38)

Related Items

Positive-instantaneous frequency and approximation ⋮ A Theory on Non-Constant Frequency Decompositions and Applications ⋮ Mathematical theory of signal analysis vs. complex analysis method of harmonic analysis

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bedrosian identity in Blaschke product case
• Translation invariant spaces
• Moduli and arguments of analytic functions from subspaces in \(H^ p\) that are invariant for the backward shift operator
• The Bedrosian identity for \(\mathbf H^p\) functions
• The Bedrosian identity and homogeneous semi-convolution equations
• Analytic approximation of matrix functions in \(L^p\)
• Phase retrieval techniques for radar ambiguity problems
• Differentiation in star-invariant subspaces. I: Boundedness and compactness
• Rational orthogonal bases satisfying the Bedrosian identity
• Adaptive Fourier series---a variation of greedy algorithm
• Characterization of boundary values of functions in Hardy spaces with applications in signal analysis
• Fourier spectrum characterization of Hardy spaces and applications
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
• Analytic Phase Derivatives, All-Pass Filters and Signals of Minimum Phase
• The Bedrosian identity for the Hilbert transform of product functions
• Mono‐components for decomposition of signals