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 "youla coding and computation of gaussian feedback capacity"):
  Abstract: In this paper, we propose an approach to numerically compute the feedback capacity of stationary finite dimensional Gaussian channels and construct (arbitrarily close to) capacity-achieving feedback codes. In particular, we first extend the interpretation of feedback communication over stationary finite dimensional Gaussian channels as feedback control systems by showing that, the problem of finding stabilizing feedback controllers with maximal reliable transmission rate over Youla parameters coincides with the problem of finding strictly causal filters to achieve feedback capacity derived in [2]. This extended interpretation provides an approach to construct deterministic feedback coding schemes with double exponential decaying error probability. We next propose asymptotic capacity-achieving upper bounds, which can be numerically evaluated by solving finite dimensional convex optimizations. From the filters that achieve the upper bounds, we apply the Youla-based interpretation to construct feasible filters, i.e., feedback codes, leading to a sequence of lower bounds. We prove the sequence of lower bounds is asymptotically capacity-achieving.

Includes members:
  Member "control approach to computing the feedback capacity for stationary finite dimensional gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "secrecy capacity of colored gaussian noise channels with feedback")
  Member "upper bound on the capacity of gaussian channels with noisy feedback":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "control approach to computing the feedback capacity for stationary finite dimensional gaussian channels")
  Member "bounds on the achievable rate of noisy feedback gaussian channels under linear feedback coding scheme":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "control approach to computing the feedback capacity for stationary finite dimensional gaussian channels")
  Member "lqg control approach to gaussian broadcast channels with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the energy distortion tradeoff of gaussian broadcast channels with feedback")
  Member "interpretations of directed information in portfolio theory data compression and hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "capacity of continuous channels with memory via directed information neural estimator")
  Member "optimal feedback communication via posterior matching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "feedback channel communication with low precision arithmetic")
  Member "convergence of fundamental limitations in feedback communication estimation and feedback control over gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a connection between feedback capacity and kalman filter for colored gaussian noises")
  Member "on the feedback capacity of power constrained gaussian noise channels with memory":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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)