human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "delayed feedback capacity of stationary sources over linear gaussian noise channels"):
  Abstract: We consider a linear Gaussian noise channel used with delayed feedback. The channel noise is assumed to be a ARMA (autoregressive and/or moving average) process. We reformulate the Gaussian noise channel into an intersymbol interference channel with white noise, and show that the delayed-feedback of the original channel is equivalent to the instantaneous-feedback of the derived channel. By generalizing results previously developed for Gaussian channels with instantaneous feedback and applying them to the derived intersymbol interference channel, we show that conditioned on the delayed feedback, a conditional Gauss-Markov source achieves the feedback capacity and its Markov memory length is determined by the noise spectral order and the feedback delay. A Kalman-Bucy filter is shown to be optimal for processing the feedback. The maximal information rate for stationary sources is derived in terms of channel input power constraint and the steady state solution of the Riccati equation of the Kalman-Bucy filter used in the feedback loop.

Includes members:
  Member "on the feedback capacity of power constrained gaussian noise channels with memory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity of continuous channels with memory via directed information neural estimator")
  Member "feedback capacity of the first order moving average gaussian channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity of continuous channels with memory via directed information neural estimator")

Question: Please tell me which class the source paper 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)