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 "a survey on deep learning based brain computer interface recent advances and new frontiers"):
  Abstract: Brain-Computer Interface (BCI) bridges the human's neural world and the outer physical world by decoding individuals' brain signals into commands recognizable by computer devices. Deep learning has lifted the performance of brain-computer interface systems significantly in recent years. In this article, we systematically investigate brain signal types for BCI and related deep learning concepts for brain signal analysis. We then present a comprehensive survey of deep learning techniques used for BCI, by summarizing over 230 contributions most published in the past five years. Finally, we discuss the applied areas, opening challenges, and future directions for deep learning-based BCI.

Includes members:
  Member "deep learning based electroencephalography analysis a systematic review":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine learning for predicting epileptic seizures using eeg signals a review")
  Member "adversarial variational embedding for robust semi supervised learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "know your mind adaptive brain signal classification with reinforced attentive convolutional neural networks")
  Member "spatial temporal recurrent neural network for emotion recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "la furca iterative context aware end to end monaural speech separation based on dual path deep parallel inter intra bi lstm with attention")
  Member "an automated system for epilepsy detection using eeg brain signals based on deep learning approach":
    also connected through other hyperedges:
      (none)
  Member "on the classification of ssvep based dry eeg signals via convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using variable natural environment brain computer interface stimuli for real time humanoid robot navigation")
  Member "eegnet a compact convolutional neural network for eeg based brain computer interfaces":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ultra efficient transfer learning with meta update for cross subject eeg classification")
  Member "compact convolutional neural networks for classification of asynchronous steady state visual evoked potentials":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards a fast steady state visual evoked potentials ssvep brain computer interface bci")
  Member "hierarchical internal representation of spectral features in deep convolutional networks trained for eeg decoding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "intracranial error detection via deep learning")

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.HC(Human-Computer Interaction)