human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "on unlimited sampling"
  Abstract: Shannon's sampling theorem provides a link between the continuous and the discrete realms stating that bandlimited signals are uniquely determined by its values on a discrete set. This theorem is realized in practice using so called analog-to-digital converters (ADCs). Unlike Shannon's sampling theorem, the ADCs are limited in dynamic range. Whenever a signal exceeds some preset threshold, the ADC saturates, resulting in aliasing due to clipping. The goal of this paper is to analyze an alternative approach that does not suffer from these problems. Our work is based on recent developments in ADC design, which allow for ADCs that reset rather than to saturate, thus producing modulo samples. An open problem that remains is: Given such modulo samples of a bandlimited function as well as the dynamic range of the ADC, how can the original signal be recovered and what are the sufficient conditions that guarantee perfect recovery? In this paper, we prove such sufficiency conditions and complement them with a stable recovery algorithm. Our results are not limited to certain amplitude ranges, in fact even the same circuit architecture allows for the recovery of arbitrary large amplitudes as long as some estimate of the signal norm is available when recovering. Numerical experiments that corroborate our theory indeed show that it is possible to perfectly recover function that takes values that are orders of magnitude higher than the ADC's threshold.

Connected through hyperedge HE-1 (induced by source paper "sampling and super resolution of sparse signals beyond the fourier domain"):
  with members:
    - "a sampling framework for solving physics driven inverse source problems"
    - "shift invariant and sampling spaces associated with the special affine fourier transform"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "frida fri based doa estimation for arbitrary array layouts"
    - "a theory of super resolution from short time fourier transform measurements"
    - "identification of linear time varying systems through waveform diversity"
    - "super resolution in phase space"
    - "sparse phase retrieval from short time fourier measurements"

Connected through hyperedge HE-2 (induced by source paper "on unlimited sampling and reconstruction"):
  with members:
    - "blind unwrapping of modulo reduced gaussian vectors recovering msbs from lsbs"
    - "above the nyquist rate modulo folding does not hurt"
    - "a modulo based architecture for analog to digital conversion"
    - "integer forcing linear receivers"

Connected through hyperedge HE-3 (induced by source paper "blind unwrapping of modulo reduced gaussian vectors recovering msbs from lsbs"):
  with members:
    - "a modulo based architecture for analog to digital conversion"
    - "integer forcing source coding"
    - "universal rate efficient scalar quantization"

Connected through hyperedge HE-4 (induced by source paper "above the nyquist rate modulo folding does not hurt"):
  with members:
    - "blind unwrapping of modulo reduced gaussian vectors recovering msbs from lsbs"
    - "a modulo based architecture for analog to digital conversion"
    - "integer forcing source coding"

Connected through hyperedge HE-5 (induced by source paper "a modulo based architecture for analog to digital conversion"):
  with members:
    - "performance analysis and optimal filter design for sigma delta modulation via duality with dpcm"
    - "massive mimo for next generation wireless systems"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "integer forcing source coding"
    - "an algebraic approach to physical layer network coding"
    - "compute and forward strategies for cooperative distributed antenna systems"
    - "universal rate efficient scalar quantization"
    - "from theory to practice sub nyquist sampling of sparse wideband analog signals"

Question: Please tell me which class the center node 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)