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 "neuromorphic electronic systems for reservoir computing"):
  Abstract: This chapter provides a comprehensive survey of the researches and motivations for hardware implementation of reservoir computing (RC) on neuromorphic electronic systems. Due to its computational efficiency and the fact that training amounts to a simple linear regression, both spiking and non-spiking implementations of reservoir computing on neuromorphic hardware have been developed. Here, a review of these experimental studies is provided to illustrate the progress in this area and to address the technical challenges which arise from this specific hardware implementation. Moreover, to deal with challenges of computation on such unconventional substrates, several lines of potential solutions are presented based on advances in other computational approaches in machine learning. #R##N#keywords: Analog Microchips, FPGA, Memristors, Neuromorphic Architectures, Reservoir Computing

Includes members:
  Member "recent advances in physical reservoir computing a review":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "advectivenet an eulerian lagrangian fluidic reservoir for point cloud processing")
  Member "computing optimal discrete readout weights in reservoir computing is np hard":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "network structure effects in reservoir computers")
  Member "a scalable multicore architecture with heterogeneous memory structures for dynamic neuromorphic asynchronous processors dynaps":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a supervised learning algorithm for multilayer spiking neural networks based on temporal coding toward energy efficient vlsi processor design")
  Member "a survey of neuromorphic computing and neural networks in hardware":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a supervised learning algorithm for multilayer spiking neural networks based on temporal coding toward energy efficient vlsi processor design")
  Member "an online structural plasticity rule for generating better reservoirs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dendritic inspired processing enables bio plausible stdp in compound binary synapses")
  Member "memory and information processing in neuromorphic systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "precise neural network computation with imprecise analog devices")
  Member "liquid state machine with dendritically enhanced readout for low power neuromorphic vlsi implementations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances in physical reservoir computing a review")

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)