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: "moment based bound on peak to average power ratio and reduction with unitary matrix"
  Abstract: Reducing Peak-to-Average Power Ratio (PAPR) is a significant task in OFDM systems. To evaluate the efficiency of PAPR-reducing methods, the complementary cumulative distribution function (CCDF) of PAPR is often used. In the situation where the central limit theorem can be applied, an approximate form of the CCDF has been obtained. On the other hand, in general situations, the bound of the CCDF has been obtained under some assumptions. In this paper, we derive the bound of the CCDF with no assumption about modulation schemes. Therefore, our bound can be applied with any codewords and that our bound is written with fourth moments of codewords. Further, we propose a method to reduce the bound with unitary matrices. With this method, it is shown that our bound is closely related to the CCDF of PAPR.

Connected through hyperedge HE-1 (induced by source paper "bound on peak to average power ratio with moment and reduction method"):
  with members:
    - "the papr problem in ofdm transmission new directions for a long lasting problem"
    - "stochastic gradient descent for non smooth optimization convergence results and optimal averaging schemes"

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)