human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the statistical restricted isometry property and the wigner semicircle distribution of incoherent dictionaries"
  Abstract: In this article we present a statistical version of the Candes-Tao restricted isometry property (SRIP for short) which holds in general for any incoherent dictionary which is a disjoint union of orthonormal bases. In addition, we show that, under appropriate normalization, the eigenvalues of the associated Gram matrix fluctuate around 1 according to the Wigner semicircle distribution. The result is then applied to various dictionaries that arise naturally in the setting of finite harmonic analysis, giving, in particular, a better understanding on a remark of Applebaum-Howard-Searle-Calderbank concerning RIP for the Heisenberg dictionary of chirp like functions.

Connected through hyperedge HE-1 (induced by source paper "random subsets of structured deterministic frames have manova spectra"):
  with members:
    - "analog coding of a source with erasures"
    - "the restricted isometry property of subsampled fourier matrices"
    - "restricted isometry of fourier matrices and list decodability of random linear codes"
    - "new constructions of rip matrices with fast multiplication and fewer rows"
    - "the restricted isometry property for time frequency structured random matrices"
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"
    - "asymptotic behaviour of random vandermonde matrices with entries on the unit circle"

Connected through hyperedge HE-2 (induced by source paper "near optimal binary compressed sensing matrix"):
  with members:
    - "ldpc codes for compressed sensing"
    - "sparse vector distributions and recovery from compressed sensing"
    - "sparse reconstruction via the reed muller sieve"
    - "compressed sensing how sharp is the restricted isometry property"
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"
    - "deterministic construction of binary bipolar and ternary compressed sensing matrices"
    - "subspace pursuit for compressive sensing signal reconstruction"
    - "iterative hard thresholding for compressed sensing"

Connected through hyperedge HE-3 (induced by source paper "sparse approximation property and stable recovery of sparse signals from noisy measurements"):
  with members:
    - "lower bounds for sparse recovery"
    - "recovery of sparsest signals via ell q minimization"
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"
    - "combining geometry and combinatorics a unified approach to sparse signal recovery"

Connected through hyperedge HE-4 (induced by source paper "on the construction of finite oscillator dictionary"):
  with members:
    - "a note on the diagonalization of the discrete fourier transform"
    - "on some deterministic dictionaries supporting sparsity"
    - "the finite harmonic oscillator and its applications to sequences communication and radar"
    - "new sequences design from weil representation with low two dimensional correlation in both time and phase shifts"
    - "on the diagonalization of the discrete fourier transform"

Connected through hyperedge HE-5 (induced by source paper "reed muller sensing matrices and the lasso"):
  with members:
    - "sparse reconstruction via the reed muller sieve"
    - "the sparsity gap uncertainty principles proportional to dimension"
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"
    - "combining geometry and combinatorics a unified approach to sparse signal recovery"

Connected through hyperedge HE-6 (induced by source paper "orthogonal symmetric toeplitz matrices for compressed sensing statistical isometry property"):
  with members:
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"
    - "deterministic designs with deterministic guarantees toeplitz compressed sensing matrices sequence designs and system identification"

Connected through hyperedge HE-7 (induced by source paper "turbo analog error correcting codes decodable by linear programming"):
  with members:
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)