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: "eigenvalue estimates and mutual information for the linear time varying channel"
  Abstract: We consider linear time-varying channels with additive white Gaussian noise. For a large class of such channels we derive rigorous estimates of the eigenvalues of the correlation matrix of the effective channel in terms of the sampled time-varying transfer function and, thus, provide a theoretical justification for a relationship that has been frequently observed in the literature. We then use this eigenvalue estimate to derive an estimate of the mutual information of the channel. Our approach is constructive and is based on a careful balance of the tradeoff between approximate operator diagonalization, signal dimension loss, and accuracy of eigenvalue estimates.

Connected through hyperedge HE-1 (induced by source paper "waterfilling theorems for linear time varying channels and related nonstationary sources"):
  with members:
    - "the distortion rate function of cyclostationary gaussian processes"
    - "waterfilling theorems in the time frequency plane for the heat channel and a related source"
    - "noncoherent capacity of underspread fading channels"

Connected through hyperedge HE-2 (induced by source paper "waterfilling theorems in the time frequency plane for the heat channel and a related source"):
  with members:
    - "the szeg o asymptotics for doubly dispersive gaussian channels"
    - "on the capacity of the heat channel waterfilling in the time frequency plane and a c node relationship"

Connected through hyperedge HE-3 (induced by source paper "on the capacity of the heat channel waterfilling in the time frequency plane and a c node relationship"):
  with members:
    - "the szeg o asymptotics for doubly dispersive gaussian channels"
    - "mutual information and minimum mean square error in gaussian channels"

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)