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 "sub nyquist sampling of short pulses"):
  Abstract: We develop sub-Nyquist sampling systems for analog signals comprised of several, possibly overlapping, finite duration pulses with unknown shapes and time positions. Efficient sampling schemes when either the pulse shape or the locations of the pulses are known have been previously developed. To the best of our knowledge, stable and low-rate sampling strategies for continuous signals that are superpositions of unknown pulses without knowledge of the pulse locations have not been derived. The goal in this paper is to fill this gap. We propose a multichannel scheme based on Gabor frames that exploits the sparsity of signals in time and enables sampling multipulse signals at sub-Nyquist rates. Moreover, if the signal is additionally essentially multiband, then the sampling scheme can be adapted to lower the sampling rate without knowing the band locations. We show that, with proper preprocessing, the necessary Gabor coefficients, can be recovered from the samples using standard methods of compressed sensing. In addition, we provide error estimates on the reconstruction and analyze the proposed architecture in the presence of noise.

Includes members:
  Member "innovation rate sampling of pulse streams with application to ultrasound imaging":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sampling and super resolution of sparse signals beyond the fourier domain")
  Member "sampling and recovery of pulse streams":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bilinear recovery using adaptive vector amp")
  Member "identification of parametric underspread linear systems and super resolution radar":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a general and yet efficient scheme for sub nyquist radar processing")
  Member "multichannel sampling of pulse streams at the rate of innovation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sub nyquist sar via fourier domain range doppler processing")
  Member "xampling signal acquisition and processing in union of subspaces":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast compressed power spectrum estimation towards a practical solution for wideband spectrum sensing")
  Member "recovering signals from lowpass data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "system approximations and generalized measurements in modern sampling theory")
  Member "time delay estimation from low rate samples a union of subspaces approach":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sampling and super resolution of sparse signals beyond the fourier domain")
  Member "rank awareness in joint sparse recovery":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a dimension reduction based joint activity detection and channel estimation algorithm for massive access")

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)