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: "a proposal for energy efficient cellular neural network based on spintronic devices"
  Abstract: Due to the massive parallel computing capability and outstanding image and signal processing performance, cellular neural network (CNN) is one promising type of non-Boolean computing system that can outperform the traditional digital logic computation and mitigate the physical scaling limit of the conventional CMOS technology. The CNN was originally implemented by VLSI analog technologies with operational amplifiers and operational transconductance amplifiers as neurons and synapses, respectively, which are power and area consuming. In this paper, we propose a hybrid structure to implement the CNN with magnetic components and CMOS peripherals with a complete driving and sensing circuitry. In addition, we propose a digitally programmable magnetic synapse that can achieve both positive and negative values of the templates. After rigorous performance analyses and comparisons, optimal energy is achieved based on various design parameters, including the driving voltage and the CMOS driving size. At a comparable footprint area and operation speed, a spintronic CNN is projected to achieve about one order of magnitude energy reduction per operation compared to its CMOS counterpart.

Connected through hyperedge HE-1 (induced by source paper "convolutional neural networks utilizing multifunctional spin hall mtj neurons"):
  with members:
    - "a mixed signal architecture for convolutional neural networks"
    - "encoding neural and synaptic functionalities in electron spin a pathway to efficient neuromorphic computing"

Connected through hyperedge HE-2 (induced by source paper "application level studies of cellular neural network based hardware accelerators"):
  with members:
    - "online tracking by learning discriminative saliency map with convolutional neural network"
    - "robust visual tracking via convolutional networks"

Connected through hyperedge HE-3 (induced by source paper "opening the doors to dynamic camouflaging harnessing the power of polymorphic devices"):
  with members:
    - "advancing hardware security using polymorphic and stochastic spin hall effect devices"
    - "logic locking for secure outsourced chip fabrication a new attack and provably secure defense mechanism"

Connected through hyperedge HE-4 (induced by source paper "benchmarking inverse rashba edelstein magnetoelectric devices for neuromorphic computing"):
  with members:
    - "comet composite input magnetoelectric based logic technology"
    - "ising spin model using spin hall effect she induced magnetization reversal in magnetic tunnel junction"

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.ET(Emerging Technologies)