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 "analog to digital compression a new paradigm for converting signals to bits"):
  Abstract: Processing, storing, and communicating information that originates as an analog signal involves converting this information to bits. This conversion can be described by the combined effect of sampling and quantization, as shown in Figure 1. The digital representation is achieved by first sampling the analog signal to represent it by a set of discretetime samples and then quantizing these samples to a finite number of bits. Traditionally, these two operations are considered separately. The sampler is designed to minimize the information loss due to sampling based on characteristics of the continuoustime input. The quantizer is designed to represent the samples as accurately as possible, subject to a constraint on the number of bits that can be used in the representation. The goal of this article is to revisit this paradigm by illuminating the dependency between these two operations. In particular, we explore the requirements of the sampling system subject to the constraints on the available number of bits for storing, communicating, or processing the analog information.

Includes members:
  Member "the distortion rate function of sampled wiener processes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")
  Member "fundamental distortion limits of analog to digital compression":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")
  Member "distortion rate function of sub nyquist sampled gaussian sources":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "system aware compression")
  Member "the distortion rate function of cyclostationary gaussian processes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the rate distortion function of asynchronously sampled memoryless cyclostationary gaussian processes")
  Member "channel capacity under sub nyquist nonuniform sampling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")
  Member "speech recognition with deep recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "centrality graph convolutional networks for skeleton based action recognition")
  Member "randomized algorithms for matrices and data":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "solving tall dense linear programs in nearly linear time")

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)