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 the finiteness of the capacity of continuous channels"
  Abstract: Evaluating the channel capacity is one of many key problems in information theory. In this work, we derive rather-mild sufficient conditions under which the capacity of continuous channels is  finite  and  achievable . These conditions are derived for generic, memoryless, and possibly nonlinear additive noise channels. The results are based on a novel sufficient condition that guarantees the convergence of differential entropies under point-wise convergence of probability density functions. Perhaps surprisingly, the finiteness of channel capacity holds for the majority of setups, including those where inputs and outputs have possibly infinite second-moments.

Connected through hyperedge HE-1 (induced by source paper "capacity achieving input distributions in nondispersive optical fibers"):
  with members:
    - "on properties of the support of capacity achieving distributions for additive noise channel models with input cost constraints"
    - "the asymptotic capacity of the optical fiber"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "information theoretic proofs of entropy power inequalities"
    - "the noncoherent rician fading channel part i structure of the capacity achieving input"

Connected through hyperedge HE-2 (induced by source paper "on properties of the support of capacity achieving distributions for additive noise channel models with input cost constraints"):
  with members:
    - "conditions for a monotonic channel capacity"
    - "information theoretic proofs of entropy power inequalities"

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)