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: "on the minimum distance of array based spatially coupled low density parity check codes"
  Abstract: An array low-density parity-check (LDPC) code is a quasi-cyclic LDPC code specified by two integers q and m, where q is an odd prime and m ≤ q. The exact minimum distance, for small q and m, has been calculated, and tight upper bounds on it for m ≤ 7 have been derived. In this work, we study the minimum distance of the spatially-coupled version of these codes. In particular, several tight upper bounds on the optimal minimum distance for coupling length at least two and m = 3; 4; 5, that are independent of q and that are valid for all values of q ≥ q 0  where q 0  depends on m, are presented. Furthermore, we show by exhaustive search that by carefully selecting the edge spreading or unwrapping procedure, the minimum distance (when q is not very large) can be significantly increased, especially for m = 5.

Connected through hyperedge HE-1 (induced by source paper "algebraic optimization of binary spatially coupled measurement matrices for interval passing"):
  with members:
    - "failure analysis of the interval passing algorithm for compressed sensing"
    - "a generalized algebraic approach to optimizing sc ldpc codes"
    - "on failing sets of the interval passing algorithm for compressed sensing"
    - "verification based interval passing algorithm for compressed sensing"
    - "a simple message passing algorithm for compressed sensing"
    - "the effect of spatial coupling on compressive sensing"
    - "optimally tuned iterative reconstruction algorithms for compressed sensing"
    - "message passing algorithms for compressed sensing i motivation and construction"

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)