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: "design and synthesis of ultralow energy spin memristor threshold logic"
  Abstract: A threshold logic gate performs weighted sum of multiple inputs and compares the sum with a threshold. We propose spin-memeristor threshold logic (SMTL) gates, which employ a memristive cross-bar array to perform current-mode summation of binary inputs, whereas the low-voltage fast-switching spintronic threshold devices carry out the threshold operation in an energy efficient manner. Field-programmable SMTL gate arrays can operate at a small terminal voltage of ∼50 mV, resulting in ultralow power consumption in gates as well as programmable interconnect networks. We evaluate the performance of SMTL using threshold logic synthesis. Results for common benchmarks show that SMTL-based programmable logic hardware can be more than 100 × energy efficient than the state-of-the-art CMOS field-programmable gate array.

Connected through hyperedge HE-1 (induced by source paper "fully memristive neural network merging image preprocessing and pattern recognition"):
  with members:
    - "a hardware friendly unsupervised memristive neural network with weight sharing mechanism"
    - "fully memristive spiking neuron learning framework and its applications on pattern recognition and edge detection"
    - "a survey of neuromorphic computing and neural networks in hardware"

Connected through hyperedge HE-2 (induced by source paper "semi trained memristive crossbar computing engine with in situ learning accelerator"):
  with members:
    - "vlsi extreme learning machine a design space exploration"
    - "memory and information processing in neuromorphic systems"
    - "training and operation of an integrated neuromorphic network based on metal oxide memristors"

Connected through hyperedge HE-3 (induced by source paper "a survey of memristive threshold logic circuits"):
  with members:
    - "memristive threshold logic circuit design of fast moving object detection"
    - "threshold logic computing memristive cmos circuits for fast fourier transform and vedic multiplication"
    - "resistive threshold logic"
    - "ultra low energy high performance dynamic resistive threshold logic"
    - "cognitive memory network"

Connected through hyperedge HE-4 (induced by source paper "stt snn a spin transfer torque based soft limiting non linear neuron for low power artificial neural networks"):
  with members:
    - "hierarchical temporal memory based on spin neurons and resistive memory for energy efficient brain inspired computing"

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)