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: "on bandlimited signal reconstruction from the distribution of unknown sampling locations"
  Abstract: In remote sensing with a large array of spatially distributed sensors, localization of individual sensor nodes could be difficult. Motivated by the smart-dust paradigm, this work addresses the reconstruction of spatially bandlimited fields from samples taken at unknown but statistically distributed sampling locations. Periodic one-dimensional bandlimited fields are considered for sampling. Samples of the field at uniform independent and identically distributed locations are obtained. The statistical realization of the sampling locations is not known. First, it is shown that a bandlimited field cannot be uniquely determined with samples taken at uniformly distributed but unknown locations, even if the number of samples is infinite. Next, it is assumed that the order of sample locations is known. With order information on sample locations, consistent bandlimited field estimates are designed and analyzed for mean-squared error. The proposed estimates are analyzed for mean-squared error for two cases—when the field measurements are noiseless and when the field measurements are affected by additive independent noise process with finite variance. Finally, a central-limit is established for the field estimate in the case where field measurements are noiseless.

Connected through hyperedge HE-1 (induced by source paper "on bandlimited field estimation from samples recorded by a location unaware mobile sensor"):
  with members:
    - "sampling and reconstruction of spatial fields using mobile sensors"
    - "performance of linear field reconstruction techniques with noise and uncertain sensor locations"

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.IT(Information Theory)