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 survey of memristive threshold logic circuits"
  Abstract: In this paper, we review different memristive threshold logic (MTL) circuits that are inspired from the synaptic action of the flow of neurotransmitters in the biological brain. The brainlike generalization ability and the area minimization of these threshold logic circuits aim toward crossing Moore’s law boundaries at device, circuits, and systems levels. Fast switching memory, signal processing, control systems, programmable logic, image processing, reconfigurable computing, and pattern recognition are identified as some of the potential applications of MTL systems. The physical realization of nanoscale devices with memristive behavior from materials, such as TiO2, ferroelectrics, silicon, and polymers, has accelerated research effort in these application areas, inspiring the scientific community to pursue the design of high-speed, low-cost, low-power, and high-density neuromorphic architectures.

Connected through hyperedge HE-1 (induced by source paper "neuromemristive circuits for edge computing a review"):
  with members:
    - "long short term memory networks in memristor crossbar arrays"
    - "learning in memristive neural network architectures using analog backpropagation circuits"
    - "neuron inspired data encoding memristive multi level memory cell"
    - "hierarchical temporal memory using memristor networks a survey"
    - "binary weighted memristive analog deep neural network for near sensor edge processing"
    - "design of cmos memristor circuits for lstm architecture"
    - "memristive lstm network hardware architecture for time series predictive modeling problem"
    - "approximate probabilistic neural networks with gated threshold logic"

Connected through hyperedge HE-2 (induced by source paper "practical implementation of memristor based threshold logic gates"):
  with members:
    - "programmable memristive threshold logic gate array"
    - "mixed precision in memory computing"
    - "hierarchical temporal memory using memristor networks a survey"
    - "approximate probabilistic neural networks with gated threshold logic"
    - "memristor threshold logic an overview to challenges and applications"
    - "a reconfigurable fir filter with memristor based weights"
    - "voltage controlled memristor threshold logic gates"
    - "memristive threshold logic circuit design of fast moving object detection"

Connected through hyperedge HE-3 (induced by source paper "hierarchical temporal memory using memristor networks a survey"):
  with members:
    - "feature extraction without learning in an analog spatial pooler memristive cmos circuit design of hierarchical temporal memory"
    - "on chip face recognition system design with memristive hierarchical temporal memory"
    - "hierarchical temporal memory based on spin neurons and resistive memory for energy efficient brain inspired computing"
    - "non volatile hierarchical temporal memory hardware for spatial pooling"
    - "continuous online sequence learning with an unsupervised neural network model"

Connected through hyperedge HE-4 (induced by source paper "a memristor based unsupervised neuromorphic system towards fast and energy efficient gan"):
  with members:
    - "convolutional networks for fast energy efficient neuromorphic computing"
    - "unsupervised representation learning with deep convolutional generative adversarial networks"
    - "lsun construction of a large scale image dataset using deep learning with humans in the loop"
    - "deep residual learning for image recognition"
    - "fast r cnn"

Connected through hyperedge HE-5 (induced by source paper "programmable memristive threshold logic gate array"):
  with members:
    - "voltage controlled memristor threshold logic gates"

Connected through hyperedge HE-6 (induced by source paper "critical neuromorphic computing based on explosive synchronization"):
  with members:
    - "computing with dynamical systems based on insulator metal transition oscillators"

Connected through hyperedge HE-7 (induced by source paper "memristive system design for variable pixel g neighbor denoising filter"):
  with members:
    - "voltage controlled memristor threshold logic gates"
    - "threshold logic computing memristive cmos circuits for fast fourier transform and vedic multiplication"
    - "resistive threshold logic"
    - "a biomimetic model of the outer plexiform layer by incorporating memristive devices"

Connected through hyperedge HE-8 (induced by source paper "on chip face recognition system design with memristive hierarchical temporal memory"):
  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)