human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "learning in memristive neural network architectures using analog backpropagation circuits"):
  Abstract: The on-chip implementation of learning algorithms would speed up the training of neural networks in crossbar arrays. The circuit level design and implementation of a back-propagation algorithm using gradient descent operation for neural network architectures is an open problem. In this paper, we propose analog backpropagation learning circuits for various memristive learning architectures, such as deep neural network, binary neural network, multiple neural network, hierarchical temporal memory, and long short-term memory. The circuit design and verification are done using TSMC 180-nm CMOS process models and TiO2-based memristor models. The application level validations of the system are done using XOR problem, MNIST character, and Yale face image databases.

Includes members:
  Member "neuromemristive circuits for edge computing a review":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an overview of memristive cryptography")
  Member "neuron inspired data encoding memristive multi level memory cell":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neuromemristive circuits for edge computing a review")
  Member "hierarchical temporal memory using memristor networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "neuromemristive circuits for edge computing a review")
  Member "binary weighted memristive analog deep neural network for near sensor edge processing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neuromemristive circuits for edge computing a review")
  Member "design of cmos memristor circuits for lstm architecture":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "neuromemristive circuits for edge computing a review")
  Member "lstm a search space odyssey":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "refined gate a simple and effective gating mechanism for recurrent units")
  Member "on chip face recognition system design with memristive hierarchical temporal memory":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "neuromemristive circuits for edge computing a review")
  Member "analog cmos based resistive processing unit for deep neural network training":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mixed precision deep learning based on computational memory")

Question: Please tell me which class the source paper 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)