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 "on the d dimensional quasi equally spaced sampling"):
  Abstract: We study a class of random matrices that appear in several communication and signal processing applications, and whose asymptotic eigenvalue distribution is closely related to the reconstruction error of an irregularly sampled bandlimited signal. We focus on the case where the random variables characterizing these matrices are d-dimensional vectors, independent, and quasi-equally spaced, i.e., they have an arbitrary distribution and their averages are vertices of a d-dimensional grid. Although a closed form expression of the eigenvalue distribution is still unknown , under these conditions we are able (i) to derive the distribution moments as the matrix size grows to infinity , while its aspect ratio is kept constant, and      

Includes members:
  Member "performance of linear field reconstruction techniques with noise and uncertain sensor locations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on bandlimited field estimation from samples recorded by a location unaware mobile sensor")
  Member "reconstruction of multidimensional signals from irregular noisy samples":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatial degrees of freedom of mimo systems in line of sight environment")
  Member "random vandermonde matrices part ii applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "massive mimo testbed implementation and initial results in system model validation")
  Member "random vandermonde matrices part i fundamental results":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the impact of physical channel on performance of subspace based channel estimation in massive mimo systems")
  Member "free deconvolution for signal processing applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "convolution operations arising from vandermonde 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)