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: "incoherent dictionaries and the statistical restricted isometry property"
  Abstract: In this paper we formulate and prove a statistical version of the restricted isometry property (SRIP for short) which holds in general for any incoherent dictionary D which is a disjoint union of orthonormal bases. In addition, we prove that, under appropriate normalization, the spectral distrib- ution of the associated Gram operator converges in probability to the Sato-Tate (also called semi-circle) distribution. The result is then applied to various dic- tionaries that arise naturally in the setting of …nite harmonic analysis, giving, in particular, a better understanding on a conjecture of Calderbank concerning RIP for the Heisenberg dictionary of chirp like functions.

Connected through hyperedge HE-1 (induced by source paper "analog coding frame work"):
  with members:
    - "frame moments and welch bound with erasures"
    - "analog coding of a source with erasures"
    - "sampling versus random binning for multiple descriptions of a bandlimited source"
    - "the restricted isometry property for time frequency structured random matrices"

Connected through hyperedge HE-2 (induced by source paper "deterministic bounds for restricted isometry of compressed sensing matrices"):
  with members:
    - "improved bounds on restricted isometry constants for gaussian matrices"
    - "compressed sensing how sharp is the restricted isometry property"

Connected through hyperedge HE-3 (induced by source paper "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"):
  with members:
    - "sparse reconstruction via the reed muller sieve"
    - "compressive sensing using low density frames"
    - "subspace pursuit for compressive sensing signal reconstruction"
    - "combining geometry and combinatorics a unified approach to sparse signal recovery"

Connected through hyperedge HE-4 (induced by source paper "the statistical restricted isometry property and the wigner semicircle distribution of incoherent dictionaries"):
  with members:
    - "the finite harmonic oscillator and its associated sequences"
    - "deterministic designs with deterministic guarantees toeplitz compressed sensing matrices sequence designs and system identification"
    - "efficient and robust compressed sensing using high quality expander graphs"
    - "on some deterministic dictionaries supporting sparsity"
    - "the finite harmonic oscillator and its applications to sequences communication and radar"
    - "efficient compressed sensing using lossless expander graphs with fast bilateral quantum recovery algorithm"
    - "on the diagonalization of the discrete fourier transform"

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)