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: "spatially coupled codes and threshold saturation on intersymbol interference channels"
  Abstract: Recently, it has been observed that terminated low-density-parity-check (LDPC) convolutional codes (or spatially-coupled codes) appear to approach capacity universally across the class of binary memoryless channels. This is facilitated by the “threshold saturation” effect whereby the belief-propagation (BP) threshold of the spatially-coupled ensemble is boosted to the maximum a-posteriori (MAP) threshold of the underlying constituent ensemble. In this paper, we consider the universality of spatially-coupled codes over intersymbol-interference (ISI) channels under joint iterative decoding. More specifically, we empirically show that threshold saturation also occurs for the considered problem. This can be observed by first identifying the EXIT curve for erasure noise and the GEXIT curve for general noise that naturally obey the general area theorem. From these curves, the corresponding MAP and the BP thresholds are then numerically obtained. With the fact that regular LDPC codes can achieve the symmetric information rate (SIR) under MAP decoding, spatially-coupled codes with joint iterative decoding can universally approach the SIR of ISI channels. For the dicode erasure channel, Kudekar and Kasai recently reported very similar results based on EXIT-like curves [1].

Connected through hyperedge HE-1 (induced by source paper "comparison of the achievable rates in ofdm and single carrier modulation with i i d inputs"):
  with members:
    - "lower bounds and approximations for the information rate of the isi channel"
    - "high snr asymptotics of mutual information for discrete constellations with applications to bicm"
    - "comparison of ofdm and sc dfe capacities without channel knowledge at the transmitter"
    - "easily computed lower bounds on the information rate of intersymbol interference channels"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "hessian and concavity of mutual information differential entropy and entropy power in linear vector gaussian channels"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "a simple proof of maxwell saturation for coupled scalar recursions"):
  with members:
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "approaching the rate distortion limit with spatial coupling belief propagation and decimation"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "nonbinary spatially coupled ldpc codes on the binary erasure channel"
    - "a proof of threshold saturation for spatially coupled ldpc codes on bms channels"
    - "thresholds of spatially coupled systems via lyapunov s method"
    - "spatial coupling as a proof technique"
    - "a simple proof of threshold saturation for coupled scalar recursions"

Connected through hyperedge HE-3 (induced by source paper "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"):
  with members:
    - "approaching the rate distortion limit with spatial coupling belief propagation and decimation"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "a proof of threshold saturation for spatially coupled ldpc codes on bms channels"
    - "spatial coupling as a proof technique"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "chains of mean field models"
    - "a phenomenological study on threshold improvement via spatial coupling"

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)