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: "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels"
  Abstract: The capacity-achieving input distribution of the discrete-time, additive white Gaussian noise (AWGN) channel with an amplitude constraint is discrete and seems difficult to characterize explicitly. A dual capacity expression is used to derive analytic capacity upper bounds for scalar and vector AWGN channels. The scalar bound improves on McKellips' bound and is within 0.1 bits of capacity for all signal-to-noise ratios (SNRs). The two-dimensional bound is within 0.15 bits of capacity provably up to 4.5 dB, and numerical evidence suggests a similar gap for all SNRs.

Connected through hyperedge HE-1 (induced by source paper "computable upper bounds on the capacity of finite state channels"):
  with members:
    - "capacity of burst noise erasure channels with and without feedback and input cost"
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "an upper bound for the capacity of amplitude constrained scalar awgn channel"
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "capacity of a post channel with and without feedback"
    - "capacity and coding for the ising channel with feedback"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-2 (induced by source paper "the capacity achieving distribution for the amplitude constrained additive gaussian channel an upper bound on the number of mass points"):
  with members:
    - "upper and lower bounds on the capacity of amplitude constrained mimo channels"
    - "an upper bound for the capacity of amplitude constrained scalar awgn channel"
    - "on the capacity of vector gaussian channels with bounded inputs"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "on the capacity of mimo optical wireless channels"):
  with members:
    - "capacity results on multiple input single output wireless optical channels"
    - "upper and lower bounds on the capacity of amplitude constrained mimo channels"
    - "on the capacity of free space optical intensity channels"

Connected through hyperedge HE-4 (induced by source paper "on the capacity of the peak power constrained vector gaussian channel an estimation theoretic perspective"):
  with members:
    - "upper and lower bounds on the capacity of amplitude constrained mimo channels"
    - "on the capacity of vector gaussian channels with bounded inputs"
    - "peak to average power ratio of good codes for gaussian channel"
    - "pointwise relations between information and estimation in gaussian noise"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-5 (induced by source paper "bounds on the capacity region of the optical intensity multiple access channel"):
  with members:
    - "on the capacity of mimo optical wireless channels"
    - "on the capacity of bandlimited optical intensity channels with gaussian noise"
    - "bandlimited intensity modulation"
    - "on the capacity of free space optical intensity channels"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-6 (induced by source paper "autocorrelation function for dispersion free fiber channels with distributed amplification"):
  with members:
    - "capacity achieving input distributions in nondispersive optical fibers"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "optimal input signal distribution and per sample mutual information for nondispersive nonlinear optical fiber channel in large snr limit"
    - "on continuous time white phase noise channels"
    - "on the per sample capacity of nondispersive optical fibers"
    - "calculation of mutual information for partially coherent gaussian channels with applications to fiber optics"

Connected through hyperedge HE-7 (induced by source paper "upper and lower bounds on the capacity of amplitude constrained mimo channels"):
  with members:
    - "the capacity of gaussian mimo channels under total and per antenna power constraints"
    - "an upper bound for the capacity of amplitude constrained scalar awgn channel"
    - "interference as noise friend or foe"
    - "on the capacity of vector gaussian channels with bounded inputs"
    - "miso capacity with per antenna power constraint"
    - "on the boundedness of the support of optimal input measures for rayleigh fading channels"

Connected through hyperedge HE-8 (induced by source paper "capacity results on multiple input single output wireless optical channels"):
  with members:
    - "on the capacity of free space optical intensity channels"

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)