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: "nonanticipative rate distortion function and filtering theory a weak convergence approach"
  Abstract: In this paper the relation between nonanticipative rate distortion function (RDF) and Bayesian filtering theory is further investigated on general Polish spaces. The relation is established via an optimization on the space of conditional distributions of the so-called directed information subject to fidelity constraints. Existence of the optimal reproduction distribution of the nonanticipative RDF is shown using the topology of weak convergence of probability measures. Subsequently, we use the solution of the nonanticipative RDF to present the realization of a multidimensional partially observable source over a scalar Gaussian channel. We show that linear encoders are optimal, establishing joint source-channel coding in real-time.

Connected through hyperedge HE-1 (induced by source paper "applications of information nonanticipative rate distortion function"):
  with members:
    - "information nonanticipative rate distortion function and its applications"
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "variational equalities of directed information and applications"
    - "directed information on abstract spaces properties and extremum problems"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"

Connected through hyperedge HE-2 (induced by source paper "variational equalities of directed information and applications"):
  with members:
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "directed information on abstract spaces properties and variational equalities"
    - "nonanticipative rate distortion function for general source channel matching"
    - "directed information on abstract spaces properties and extremum problems"
    - "computable bounds for rate distortion with feed forward for stationary and ergodic sources"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"
    - "extension of the blahut arimoto algorithm for maximizing directed information"
    - "on delayed sequential coding of correlated sources"

Connected through hyperedge HE-3 (induced by source paper "on the relation of nonanticipative rate distortion function and filtering theory"):
  with members:
    - "directed information on abstract spaces properties and extremum problems"

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)