human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "variable length coding for zero error channel capacity"):
  Abstract: The zero-error channel capacity is the maximum asymptotic rate that can be reached with error probability exactly zero, instead of a vanishing error probability. The nature of this problem, essentially combinatorial rather than probabilistic, has led to various researches both in Information Theory and Combinatorics. However, the zero-error capacity is still an open problem, for example the capacity of the noisy-typewriter channel with 7 letters is unknown. In this article, we propose a new approach to construct optimal zero-error codes, based on the concatenation of words of variable-length, taken from a generator set. Three zero-error variable-length coding schemes, referred to as "variable-length coding", "intermingled coding" and "automata-based coding", are under study. We characterize their asymptotic performances via linear difference equations, in terms of simple properties of the generator set, e.g. the roots of the characteristic polynomial, the spectral radius of an adjacency matrix, the inverse of the convergence radius of a generator series. For a specific example, we construct an "intermingled" coding scheme that achieves asymptotically the zero-error capacity.

Includes members:
  Member "zero error capacity of duplication channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal codes correcting a burst of deletions of variable length")
  Member "bounds on the reliability of typewriter channels":
    also connected through other hyperedges:
      (none)
  Member "zero error capacity of p ary shift channels and fifo queues":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "runlength limited sequences and shift correcting codes asymptotic analysis")
  Member "the rho capacity of a graph":
    also connected through other hyperedges:
      (none)
  Member "uncertain wiretap channels and secure estimation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "noiseless privacy")
  Member "rate distance tradeoff for codes above graph capacity":
    also connected through other hyperedges:
      (none)
  Member "secure estimation and zero error secrecy capacity":
    also connected through other hyperedges:
      (none)
  Member "graph information ratio":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper 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)