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: "low latency sc decoder architectures for polar codes"
  Abstract: Nowadays polar codes are becoming one of the most favorable capacity achieving error correction codes for their low encoding and decoding complexity. However, due to the large code length required by practical applications, the few existing successive cancellation (SC) decoder implementations still suffer from not only the high hardware cost but also the long decoding latency. This paper presents novel several approaches to design low-latency decoders for polar codes based on look-ahead techniques. Look-ahead techniques can be employed to reschedule the decoding process of polar decoder in numerous approaches. However, among those approaches, only well-arranged ones can achieve good performance in terms of both latency and hardware complexity. By revealing the recurrence property of SC decoding chart, the authors succeed in reducing the decoding latency by 50% with look-ahead techniques. With the help of VLSI-DSP design techniques such as pipelining, folding, unfolding, and parallel processing, methodologies for four different polar decoder architectures have been proposed to meet various application demands. Sub-structure sharing scheme has been adopted to design the merged processing element (PE) for further hardware reduction. In addition, systematic methods for construction refined pipelining decoder (2nd design) and the input generating circuits (ICG) block have been given. Detailed gate-level analysis has demonstrated that the proposed designs show latency advantages over conventional ones with similar hardware cost.

Connected through hyperedge HE-1 (induced by source paper "partial sums generation architecture for successive cancellation decoding of polar codes"):
  with members:
    - "hardware implementation of successive cancellation decoders for polar codes"
    - "hardware architectures for successive cancellation decoding of polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "polarization for arbitrary discrete memoryless channels"

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.AR(Hardware Architecture)