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 "a general sequential delay doppler estimation scheme for sub nyquist pulse doppler radar"):
  Abstract: Sequential estimation of the delay and Doppler parameters for sub-Nyquist radars by analog-to-information conversion (AIC) systems has received wide attention recently. However, the estimation methods reported are AIC-dependent and have poor performance for off-grid targets. This paper develops a general estimation scheme in the sense that it is applicable to all AICs regardless whether the targets are on or off the grids. The proposed scheme estimates the delay and Doppler parameters sequentially, in which the delay estimation is formulated into a beamspace direction-of- arrival problem and the Doppler estimation is translated into a line spectrum estimation problem. Then the well-known spatial and temporal spectrum estimation techniques are used to provide efficient and high-resolution estimates of the delay and Doppler parameters. In addition, sufficient conditions on the AIC to guarantee the successful estimation of off-grid targets are provided, while the existing conditions are mostly related to the on-grid targets. Theoretical analyses and numerical experiments show the effectiveness and the correctness of the proposed scheme.

Includes members:
  Member "compressive parameter estimation for sparse translation invariant signals using polar interpolation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressive parameter estimation via k median clustering")
  Member "gridless quadrature compressive sampling with interpolated array technique":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a general and yet efficient scheme for sub nyquist radar processing")
  Member "quadrature compressive sampling for radar signals":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analysis of frequency agile radar via compressed sensing")
  Member "sub nyquist radar via doppler focusing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sampling and super resolution of sparse signals beyond the fourier domain")
  Member "identification of parametric underspread linear systems and super resolution radar":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a general and yet efficient scheme for sub nyquist radar processing")
  Member "xampling signal acquisition and processing in union of subspaces":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fast compressed power spectrum estimation towards a practical solution for wideband spectrum sensing")
  Member "beyond nyquist efficient sampling of sparse bandlimited signals":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secure and efficient compressed sensing based encryption with sparse matrices")

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)