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 "a connection between feedback capacity and kalman filter for colored gaussian noises"):
  Abstract: In this paper, we establish a connection between the feedback capacity of additive colored Gaussian noise channels and the Kalman filters with additive colored Gaussian noises. In light of this, we are able to provide lower bounds on feedback capacity of such channels with finite-order auto-regressive moving average colored noises, and the bounds are seen to be consistent with various existing results in the literature; particularly, the bound is tight in the case of first-order auto-regressive moving average colored noises. On the other hand, the Kalman filtering systems, after certain equivalence transformations, can be employed as recursive coding schemes/algorithms to achieve the lower bounds. In general, our results provide an alternative perspective while pointing to potentially tighter bounds for the feedback capacity problem.

Includes members:
  Member "generic variance bounds on estimation and prediction errors in time series analysis an entropy perspective":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fundamental limits of online learning an entropic innovations viewpoint")
  Member "youla coding and computation of gaussian feedback capacity":
    also connected through other hyperedges:
      (none)
  Member "feedback capacity of stationary gaussian channels further examined":
    also connected through other hyperedges:
      (none)
  Member "sequential necessary and sufficient conditions for capacity achieving distributions of channels with memory and feedback":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "information structures for feedback capacity of channels with memory and transmission cost stochastic optimal control variational equalities part i")
  Member "feedback capacity of gaussian channels revisited":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a kinematic information theoretic transmission scheme for goal directed movements")
  Member "information structures of capacity achieving distributions for feedback channels with memory and transmission cost stochastic optimal control variational equalities part i":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "time invariant feedback strategies do not increase capacity of agn channels driven by stable and certain unstable autoregressive noise")
  Member "capacity achieving feedback schemes for gaussian finite state markov channels with channel state information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "combining channel output feedback and csi feedback for mimo wireless systems")
  Member "convergence of fundamental limitations in feedback communication estimation and feedback control over gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "youla coding and computation of gaussian feedback capacity")

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)