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: "modal analysis using co prime arrays"
  Abstract: We address the problem of estimating mode parameters from noisy observations of a linear combination of the corresponding modes. This problem arises in line spectrum estimation, vibration analysis, speech processing, system identification, and direction of arrival estimation. Our results differ from standard results of modal analysis to the extent that we consider co-prime samplings in space, or equivalently co-prime samplings in time. Our main result is a characterization of the orthogonal subspace for this problem. This is the subspace that is orthogonal to the signal subspace spanned by the columns of the generalized Vandermonde matrix of modes in co-prime samplings. This characterization is derived in a form that allows us to adapt modern methods of subspace signal processing to co-prime sampled signals. Several numerical examples are presented to demonstrate the application of the proposed modal estimation method. We state and prove theorems on identifiability of the modes and calculate a Cramer-Rao bound that allows us to analyze the performance of co-prime arrays that are subsamplings of uniform linear arrays of the same apertures.

Connected through hyperedge HE-1 (induced by source paper "threshold effects in parameter estimation from compressed data"):
  with members:
    - "r dimensional esprit type algorithms for strictly second order non circular sources and their performance analysis"

Connected through hyperedge HE-2 (induced by source paper "doa estimation of coherent signals on coprime arrays exploiting fourth order cumulants"):
  with members:
    - "direction of arrival estimation using co prime arrays a super resolution viewpoint"

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)