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 converse bound characterization on zero delay indirect rdf for vector gauss markov sources"):
  Abstract: We consider a zero-delay remote source coding problem where a hidden source modeled as a time-invariant vector-valued Gauss-Markov process is partially observed to an encoder whereas the performance criterion is the long-term mean squared-error (MSE) distortion between the hidden process and the reconstructed process. For this setup, we characterize a converse bound on the minimum long-term average length of all causal prefix-free codes. This characterization is then used to derive a novel closed form expression for stationary scalar-valued Gaussian processes. We justify the generality of our solution by revealing well-known special cases from it like the widely used analytical expression of sequential or nonanticipative RDF derived for "fully observable" stationary scalar-valued Gauss-Markov processes with MSE distortion constraint in [1], from which we also compute analytically the rate-loss (RL) gap from our solution.

Includes members:
  Member "zero delay rate distortion via filtering for vector valued gaussian sources":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on zero delay rdf for vector valued gauss markov sources with additional noise")
  Member "optimal estimation via nonanticipative rate distortion function and applications to time varying gauss markov processes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal causal rate constrained sampling of the wiener process")
  Member "directed information on abstract spaces properties and variational equalities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on zero delay rdf for vector valued gauss markov sources with additional noise")
  Member "internet of things iot a vision architectural elements and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neuromemristive circuits for edge computing a review")
  Member "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal causal rate constrained sampling of the wiener process")

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)