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: "analysis and design of tuned turbo codes"
  Abstract: It has been widely observed that there exists a fundamental tradeoff between the minimum (Hamming) distance properties and the iterative decoding convergence behavior of turbo- like codes. While capacity-achieving code ensembles typically are asymptotically bad in the sense that their minimum distance does not grow linearly with block length, and they therefore exhibit an error floor at moderate-to-high signal-to-noise ratios, asymptotically good codes usually converge further away from channel capacity. In this paper, we introduce the concept of tuned turbo codes, a family of asymptotically good hybrid concatenated code ensembles, where asymptotic minimum distance growth rates, convergence thresholds, and code rates can be tradedoff using two tuning parameters: λ and μ. By decreasing λ, the asymptotic minimum distance growth rate is reduced in exchange for improved iterative decoding convergence behavior, while increasing λ raises the asymptotic minimum distance growth rate at the expense of worse convergence behavior, and thus, the code performance can be tuned to fit the desired application. By decreasing μ, a similar tuning behavior can be achieved for higher rate code ensembles.

Connected through hyperedge HE-1 (induced by source paper "spatially coupled turbo like codes"):
  with members:
    - "finite length weight enumerator analysis of braided convolutional codes"
    - "spatially coupled ldpc codes constructed from protographs"
    - "a simple proof of maxwell saturation for coupled scalar recursions"
    - "spatially coupled turbo codes principles and finite length performance"
    - "braided convolutional codes a class of spatially coupled turbo like codes"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "staircase codes fec for 100 gb s otn"
    - "approaching capacity at high rates with iterative hard decision decoding"

Connected through hyperedge HE-2 (induced by source paper "minimum pseudoweight analysis of 3 dimensional turbo codes"):
  with members:
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "polytope of correct linear programming decoding and low weight pseudo codewords"
    - "exposing pseudoweight layers in regular ldpc code ensembles"
    - "turbo decoding on the binary erasure channel finite length analysis and turbo stopping sets"
    - "on maximum contention free interleavers and permutation polynomials over integer rings"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"

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)