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: "tdoabased localization in two dimensions the bifurcation curve"
  Abstract: In this paper, we complete the study of the geometry of the TDOA map that encodes the noiseless model for the localization of a source from the range differences between three receivers in a plane, by computing the Cartesian equation of the bifurcation curve in terms of the positions of the receivers. From that equation, we can compute its real asymptotic lines. The present manuscript completes the analysis of [12]. Our result is useful to check if a source belongs or is closed to the bifurcation curve, where the localization in a noisy scenario is ambiguous.

Connected through hyperedge HE-1 (induced by source paper "a geometrical statistical approach to outlier removal for tdoa measurements"):
  with members:
    - "source localization and denoising a perspective from the tdoa space"
    - "on the statistical model of source localization based on range difference measurements"
    - "tdoa matrices algebraic properties and their application to robust denoising with missing data"

Connected through hyperedge HE-2 (induced by source paper "source localization and denoising a perspective from the tdoa space"):
  with members:
    - "a geometric approach to sound source localization from time delay estimates"

Connected through hyperedge HE-3 (induced by source paper "on the statistical model of source localization based on range difference measurements"):
  with members:
    - "source localization and denoising a perspective from the tdoa space"
    - "a geometrical statistical approach to outlier removal for tdoa measurements"
    - "tdoa matrices algebraic properties and their application to robust denoising with missing data"
    - "a geometric approach to sound source localization from time delay estimates"

Connected through hyperedge HE-4 (induced by source paper "tdoa denoising for acoustic source localization"):
  with members:
    - "a geometric approach to sound source localization from time delay estimates"

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)