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: "phase reconstruction of spectrograms based on a model of repeated audio events"
  Abstract: Phase recovery of modified spectrograms is a major issue in audio signal processing applications, such as source separation. This paper introduces a novel technique for estimating the phases of components in complex mixtures within onset frames in the Time-Frequency (TF) domain. We propose to exploit the phase repetitions from one onset frame to another. We introduce a reference phase which characterizes a component independently of its activation times. The onset phases of a component are then modeled as the sum of this reference and an offset which is linearly dependent on the frequency. We derive a complex mixture model within onset frames and we provide two algorithms for the estimation of the model phase parameters. The model is estimated on experimental data and this technique is integrated into an audio source separation framework. The results demonstrate that this model is a promising tool for exploiting phase repetitions, and point out its potential for separating overlapping components in complex mixtures.

Connected through hyperedge HE-1 (induced by source paper "model based stft phase recovery for audio source separation"):
  with members:
    - "multi scale multi band densenets for audio source separation"
    - "phase reconstruction of spectrograms with linear unwrapping application to audio signal restoration"
    - "single channel multi speaker separation using deep clustering"
    - "complex nmf under phase constraints based on signal modeling application to audio source separation"
    - "phase recovery in nmf for audio source separation an insightful benchmark"
    - "informed source separation using iterative reconstruction"
    - "wirtinger s calculus in general hilbert spaces"

Connected through hyperedge HE-2 (induced by source paper "phase recovery by unwrapping applications to music signal processing"):
  with members:
    - "multi scale multi band densenets for audio source separation"
    - "phase reconstruction of spectrograms with linear unwrapping application to audio signal restoration"
    - "complex nmf under phase constraints based on signal modeling application to audio source separation"
    - "phase recovery in nmf for audio source separation an insightful benchmark"
    - "wirtinger s calculus in general hilbert spaces"

Connected through hyperedge HE-3 (induced by source paper "complex nmf under phase constraints based on signal modeling application to audio source separation"):
  with members:
    - "phase reconstruction of spectrograms with linear unwrapping application to audio signal restoration"
    - "non negative matrix factorization with sparseness constraints"

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.SD(Sound)