human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "distributed compressed sensing off the grid"):
  Abstract: This letter investigates the joint recovery of a frequency-sparse signal ensemble sharing a common frequency-sparse component from the collection of their compressed measurements. Unlike conventional arts in compressed sensing, the frequencies follow an off-the-grid formulation and are continuously valued in [0, 1]. As an extension of atomic norm, the concatenated atomic norm minimization approach is proposed to handle the exact recovery of signals, which is reformulated as a computationally tractable semidefinite program. The optimality of the proposed approach is characterized using a dual certificate. Numerical experiments are performed to illustrate the effectiveness of the proposed approach and its advantage over separate recovery.

Includes members:
  Member "super resolution line spectrum estimation with block priors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "block iterative reweighted algorithms for super resolution of spectrally sparse signals")
  Member "music for single snapshot spectral estimation stability and super resolution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the stable resolution limit of total variation regularization for spike deconvolution")
  Member "direction of arrival estimation using co prime arrays a super resolution viewpoint":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "interference removal for radar communication co existence the random scattering case")
  Member "super resolution compressed sensing an iterative reweighted algorithm for joint parameter learning and sparse signal recovery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sparse methods for direction of arrival estimation")
  Member "off the grid spectral compressed sensing with prior information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "enhancing sparsity and resolution via reweighted atomic norm minimization")
  Member "spectral compressive sensing with polar interpolation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "compressive parameter estimation via k median clustering")
  Member "spectral compressed sensing via structured matrix completion":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "two dimensional super resolution via convex relaxation")
  Member "joint sparsity recovery for spectral compressed sensing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "super resolution blind channel and signal estimation for massive mimo with one dimensional antenna array")

Question: Please tell me which class the source paper 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)