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: "taylor series expansions for the entropy rate of hidden markov processes"
  Abstract: Finding the entropy rate of Hidden Markov Processes is an active research topic, of both theoretical and practical importance. A recently used approach is studying the asymptotic behavior of the entropy rate in various regimes. In this paper we generalize and prove a previous conjecture relating the entropy rate to entropies of finite systems. We use the proof to establish series expansions for the entropy rate in two different regimes. We also study the radius of convergence of the two series expansions.

Connected through hyperedge HE-1 (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"
    - "asymptotics of entropy rate in special families of hidden markov chains"
    - "derivatives of entropy rate in special families of hidden markov chains"
    - "the entropy of a binary hidden markov process"

Connected through hyperedge HE-2 (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"
    - "asymptotics of entropy rate in special families of hidden markov chains"
    - "derivatives of entropy rate in special families of hidden markov chains"
    - "the entropy of a binary hidden markov process"

Connected through hyperedge HE-3 (induced by source paper "the entropy rate of the binary symmetric channel in the rare transitions regime"):
  with members:
    - "derivatives of entropy rate in special families of hidden markov chains"
    - "the entropy of a binary hidden markov process"
    - "from finite system entropy to entropy rate for a hidden markov process"

Connected through hyperedge HE-4 (induced by source paper "derivatives of entropy rate in special families of hidden markov chains"):
  with members:
    - "the entropy of a binary hidden markov process"
    - "from finite system entropy to entropy rate for a 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)