Universal Spatiotemporal Sampling Sets for Discrete Spatially Invariant Evolution Processes

• Published in: IEEE transactions on information theory Vol. 63; no. 9; pp. 5518 - 5528
• Main Author: Tang, Sui
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Convolution; discrete fourier transform; Eigenvalues; Eigenvalues and eigenfunctions; Evolution; finite frames; full spark matrix; Interpolation; Invariants; Kernel; Mathematical analysis; Polynomials; Sampling; Sensors; Signal processing; Sparks; Spatiotemporal phenomena; Spatiotemporal sampling
• ISSN: 0018-9448; 1557-9654
• DOI: 10.1109/TIT.2017.2696019

Let (I, +) be a finite abelian group and A be a circular convolution operator on ℓ 2 (I). The problem under consideration is how to construct minimal Ω ⊂ I and l i such that Y = {e i , Ae i , · · · , A l i e i : i ∈ Ω} is a frame for ℓ 2 (I), where {e i : i ∈ I} is the canonical basis of ℓ 2 (I). This problem is motivated by the spatiotemporal sampling problem in discrete spatially invariant evolution processes. We will show that the cardinality of Ω should be at least equal to the largest geometric multiplicity of eigenvalues of A, and consider the universal spatiotemporal sampling sets (Ω, l i ) for convolution operators whose eigenvalues subject to the same largest geometric multiplicity. We will give an algebraic characterization for such sampling sets and show how this problem is linked with sparse signal processing theory and polynomial interpolation theory.