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: "asymptotics of entropy rate in special families of hidden markov chains"
  Abstract: We derive an asymptotic formula for entropy rate of a hidden Markov chain around a "weak Black Hole". We also discuss applications of the asymptotic formula to the asymptotic behaviors of certain channels.

Connected through hyperedge HE-1 (induced by source paper "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"):
  with members:
    - "asymptotics of input constrained erasure channel capacity"
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"
    - "an efficient feedback coding scheme with low error probability for discrete memoryless channels"
    - "a simple proof for the optimality of randomized posterior matching"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "capacity and coding for the ising channel with feedback"

Connected through hyperedge HE-2 (induced by source paper "asymptotics of input constrained erasure channel capacity"):
  with members:
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "the feedback capacity of the 1 rll input constrained erasure channel"
    - "derivatives of entropy rate in special families of hidden markov chains"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-3 (induced by source paper "the feedback capacity of the 1 rll input constrained erasure channel"):
  with members:
    - "constrained codes for joint energy and information transfer"
    - "capacity and coding for the ising channel with feedback"
    - "optimal feedback communication via posterior matching"
    - "feedback capacity of the compound channel"
    - "a coding theorem for a class of stationary channels with feedback"
    - "finite state channels with time invariant deterministic feedback"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-4 (induced by source paper "a randomized approach to the capacity of finite state channels"):
  with members:
    - "the bethe permanent of a nonnegative matrix"
    - "non asymptotic equipartition properties for independent and identically distributed sources"
    - "limit theorems in hidden markov models"
    - "entropy rate for hidden markov chains with rare transitions"
    - "entropy of hidden markov processes via cycle expansion"
    - "derivatives of entropy rate in special families of hidden markov chains"
    - "taylor series expansions for the entropy rate of hidden markov processes"
    - "the entropy of a binary hidden markov process"

Connected through hyperedge HE-5 (induced by source paper "entropy rate calculations of algebraic measures"):
  with members:
    - "efficient tests for equivalence of hidden markov processes and quantum random walks"
    - "on analytic properties of entropy rate"
    - "the entropy of a binary hidden markov process"

Connected through hyperedge HE-6 (induced by source paper "limit theorems in hidden markov models"):
  with members:
    - "non asymptotic equipartition properties for independent and identically distributed sources"
    - "entropy rate for hidden markov chains with rare transitions"
    - "the capacity of finite state channels in the high noise regime"
    - "concavity of mutual information rate for input restricted finite state memoryless channels at high snr"
    - "derivatives of entropy rate in special families of hidden markov chains"
    - "taylor series expansions for the entropy rate of hidden markov processes"
    - "the entropy of a binary hidden markov process"

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)