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 "model of an oscillatory neural network with multilevel neurons for pattern recognition"):
  Abstract: The article presents a study on a new type of an oscillatory neural network (ONN) that uses multilevel neurons for pattern recognition on the basis of high order synchronization effect. The feature of this network architecture is a single oscillator (neuron) at the output with multilevel variation of its synchronization value with the main oscillator thus allowing classifications of an input pattern into a set of classes. ONN model is realized on thermally-coupled VO2-oscillators. ONN training was performed by using the trial-and-error method for the network parameters selection. It is shown that ONN is capable to classify 512 visual patterns (as a cell array 3x3, distributed by symmetry into 102 classes) into a set of classes with the maximum number of elements up to P=11. Classification capability of a network is studied depending on the interior noise level and synchronization effectiveness parameter. The obtained results allow designing multilevel output cascades of neural networks with high net data throughput and it may be applied in ONNs with various coupling mechanisms and oscillators topology.

Includes members:
  Member "effects of higher order and long range synchronizations for classification and computing in oscillator based spiking neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a model of an oscillatory neural network with multilevel neurons for pattern recognition and computing")
  Member "switching dynamics of single and coupled vo2 based oscillators as elements of neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effects of higher order and long range synchronizations for classification and computing in oscillator based spiking neural networks")
  Member "thermal coupling and effect of subharmonic synchronization in a system of two vo2 based oscillators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "effects of higher order and long range synchronizations for classification and computing in oscillator based spiking neural networks")

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)