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: "the area under a receiver operating characteristic curve over enriched multipath fading conditions"
  Abstract: This work is devoted to the analysis of the performance of energy detection based spectrum sensing in the presence of enriched fading conditions which are distinct for the large number of multipath components and the lack of a dominant components. This type of fading conditions are characterized efficiently by the well known Nakagami${-}q$ or Hoyt distribution and the proposed analysis is carried out in the context of the area under the receiver operating characteristics (ROC) curve (AUC). Unlike the widely used probability of detection metric, the AUC is a single metric and has been shown to be rather capable of evaluating the performance of a detector in applications relating to cognitive radio, radar systems and biomedical engineering, among others. Based on this, novel analytic expressions are derived for the average AUC and its complementary metric, average CAUC, for both integer and fractional values of the involved time-bandwidth product. The derived expressions have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. Based on this, they are employed in analyzing the behavior of energy detection based spectrum sensing over enriched fading conditions for different severity scenarios, which demonstrates that the performance of energy detectors is, as expected, closely related to the value of the fading parameter $q$.

Connected through hyperedge HE-1 (induced by source paper "solutions to integrals involving the marcum q function and applications"):
  with members:
    - "analytic solutions to a marcum q function based integral and application in energy detection of unknown signals over multipath fading channels"
    - "novel expressions for the rice ie function and the incomplete lipschitz hankel integrals"
    - "analytic performance evaluation of underlay relay cognitive networks with channel estimation errors"
    - "analytic expressions and bounds for special functions and applications in communication theory"
    - "the effects of limited channel knowledge on cognitive radio system capacity"

Connected through hyperedge HE-2 (induced by source paper "energy detection of unknown signals over cascaded fading channels"):
  with members:
    - "analytic expressions and bounds for special functions and applications in communication theory"
    - "a new formula for the ber of binary modulations with dual branch selection over generalized k"

Connected through hyperedge HE-3 (induced by source paper "analytic expressions and bounds for special functions and applications in communication theory"):
  with members:
    - "on the bivariate nakagami m cumulative distribution function closed form expression and applications"
    - "an approximation of the first order marcum q function with application to network connectivity analysis"
    - "on the monotonicity log concavity and tight bounds of the generalized marcum and nuttall q functions"
    - "on the monotonicity of the generalized marcum and nuttall q functions"

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)