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: "average performance of orthogonal matching pursuit omp for sparse approximation"
  Abstract: We present a theoretical analysis of the average performance of orthogonal matching pursuit (OMP) for sparse approximation. For signals that are generated from a dictionary with   $K$    atoms and coherence   $\mu$    and coefficients corresponding to a geometric sequence with parameter    $\alpha   , we show that OMP is successful with high probability as long as the sparsity level   $S$   scales as   $S\mu ^2 \log K \lesssim 1-\alpha$  . This improves by an order of magnitude over worst case results and shows that OMP and its famous competitor Basis Pursuit outperform each other depending on the setting.

Connected through hyperedge HE-1 (induced by source paper "compressed sensing channel estimation for ofdm with non gaussian multipath gains"):
  with members:
    - "fast channel estimation for millimetre wave wireless systems using overlapped beam patterns"
    - "compressive channel estimation and tracking for large arrays in mm wave picocells"
    - "channel estimation for millimeter wave massive mimo with hybrid precoding over frequency selective fading channels"
    - "channel estimation for hybrid architecture based wideband millimeter wave systems"
    - "compressed sensing algorithms for ofdm channel estimation"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "distributed compressive csit estimation and feedback for fdd multi user massive mimo systems"

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)