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 "analysis and design of finite alphabet iterative decoders robust to faulty hardware"):
  Abstract: This paper addresses the problem of designing low-density parity check decoders robust to transient errors introduced by faulty hardware. We assume that the faulty hardware introduces errors during the message-passing updates, and we propose a general framework for the definition of the message update faulty functions. Within this framework, we define symmetry conditions for the faulty functions and derive two simple error models used in the analysis. With this analysis, we propose a new interpretation of the functional density evolution threshold introduced by Kameni  et al.  in the recent literature and show its limitations in the case of highly unreliable hardware. However, we show that under restricted decoder noise conditions, the functional threshold can be used to predict the convergence behavior of finite alphabet iterative decoders (FAIDs) under faulty hardware. In particular, we reveal the existence of robust and nonrobust FAIDs and propose a framework for the design of robust decoders. We finally illustrate robust- and nonrobust-decoder behaviors of finite-length codes using Monte Carlo simulations.

Includes members:
  Member "density evolution and functional threshold for the noisy min sum decoder":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "faulty successive cancellation decoding of polar codes for the binary erasure channel")
  Member "density evolution for min sum decoding of ldpc codes under unreliable message storage":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "faulty successive cancellation decoding of polar codes for the binary erasure channel")
  Member "performance of ldpc codes under faulty iterative decoding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploiting errors for efficiency a survey from circuits to algorithms")
  Member "design and analysis of nonbinary ldpc codes for arbitrary discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "lattice coding for downlink multiuser transmission")
  Member "density evolution for asymmetric memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "asymptotic analysis on ldpc bicm scheme for compute and forward relaying")

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)