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: "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
  Abstract: We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify certain characteristics of LDPC convolutional code ensembles that exhibit good performance with the windowed decoder. We will consider the performance of these ensembles and codes over erasure channels with and without memory. We show that the structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding. However, the same structure imposes limitations on the performance over erasure channels with memory.

Connected through hyperedge HE-1 (induced by source paper "finite length scaling of spatially coupled ldpc codes under window decoding over the bec"):
  with members:
    - "spatially coupled turbo like codes"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "spatially coupled sparse codes on graphs theory and practice"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "lossy source coding via spatially coupled ldgm ensembles"
    - "staircase codes fec for 100 gb s otn"
    - "information theoretically optimal compressed sensing via spatial coupling and approximate message passing"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"

Connected through hyperedge HE-2 (induced by source paper "non uniform windowed decoding for multi dimensional spatially coupled ldpc codes"):
  with members:
    - "minimizing the number of detrimental objects in multi dimensional graph based codes"
    - "finite length analysis of spatially coupled regular ldpc ensembles on burst erasure channels"
    - "new codes on graphs constructed by connecting spatially coupled chains"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "windowed decoding of spatially coupled codes"

Connected through hyperedge HE-3 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage"):
  with members:
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "spatially coupled code design for partial response channels optimal object minimization approach"
    - "a generalized algebraic approach to optimizing sc ldpc codes"
    - "high performance non binary spatially coupled codes for flash memories"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "spatially coupled ldpc codes constructed from protographs"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "iterative decoding of ldpc codes over the q ary partial erasure channel"

Connected through hyperedge HE-4 (induced by source paper "multi dimensional spatially coupled code design enhancing the cycle properties"):
  with members:
    - "efficient search and elimination of harmful objects in optimized qc sc ldpc codes"
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "multi dimensional spatially coupled code design through informed relocation of circulants"
    - "spatially coupled code design for partial response channels optimal object minimization approach"
    - "high performance non binary spatially coupled codes for flash memories"
    - "hierarchical and high girth qc ldpc codes"
    - "multi dimensional spatially coupled codes"
    - "new codes on graphs constructed by connecting spatially coupled chains"

Connected through hyperedge HE-5 (induced by source paper "one and two bit message passing for sc ldpc codes with higher order modulation"):
  with members:
    - "a novel soft aided bit marking decoder for product codes"
    - "binary message passing decoding of product like codes"
    - "protograph based ldpc code design for ternary message passing decoding"
    - "energy efficient soft assisted product decoders"
    - "information rates and error exponents for probabilistic amplitude shaping"
    - "constant composition distribution matching"
    - "staircase codes fec for 100 gb s otn"
    - "analysis and design of binary message passing decoders"

Connected through hyperedge HE-6 (induced by source paper "spatially coupled generalized ldpc codes asymptotic analysis and finite length scaling"):
  with members:
    - "a refined scaling law for spatially coupled ldpc codes over the binary erasure channel"
    - "spatially coupled ldpc codes constructed from protographs"
    - "design of ldpc code ensembles with fast convergence properties"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "on the minimum distance of generalized spatially coupled ldpc codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "maxwell construction the hidden bridge between iterative and maximum a posteriori decoding"

Connected through hyperedge HE-7 (induced by source paper "a channel aware combinatorial approach to design high performance spatially coupled codes for magnetic recording systems"):
  with members:
    - "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage"
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "spatially coupled code design for partial response channels optimal object minimization approach"
    - "high performance non binary spatially coupled codes for flash memories"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "deriving good ldpc convolutional codes from ldpc block codes"

Connected through hyperedge HE-8 (induced by source paper "design and analysis of time invariant sc ldpc convolutional codes with small constraint length"):
  with members:
    - "on advisability of designing short length qc ldpc codes using perfect difference families"
    - "spatially coupled ldpc codes constructed from protographs"
    - "construction of high rate regular quasi cyclic ldpc codes based on cyclic difference families"
    - "quasi cyclic ldpc codes influence of proto and tanner graph structure on minimum hamming distance upper bounds"
    - "progressive differences convolutional low density parity check codes"
    - "deriving good ldpc convolutional codes from ldpc block codes"
    - "terminated ldpc convolutional codes with thresholds close to capacity"

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)