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: "some results on the information loss in dynamical systems"
  Abstract: In this work we investigate the information loss in (nonlinear) dynamical input-output systems and provide some general results. In particular, we present an upper bound on the information loss rate, defined as the (non-negative) difference between the entropy rates of the jointly stationary stochastic processes at the input and output of the system. We further introduce a family of systems with vanishing information loss rate. It is shown that not only linear filters belong to that family, but — under certain circumstances — also finite-precision implementations of the latter, which typically consist of nonlinear elements.

Connected through hyperedge HE-1 (induced by source paper "lumpings of markov chains entropy rate preservation and higher order lumpability"):
  with members:
    - "information preserving markov aggregation"

Connected through hyperedge HE-2 (induced by source paper "information measures for deterministic input output systems"):
  with members:
    - "relative information loss in the pca"
    - "signal enhancement as minimization of relevant information loss"
    - "information loss in static nonlinearities"
    - "on the information loss in memoryless systems the multivariate case"
    - "optimal phase transitions in compressed sensing"
    - "a characterization of entropy in terms of information loss"

Connected through hyperedge HE-3 (induced by source paper "on the rate of information loss in memoryless systems"):
  with members:
    - "lumpings of markov chains entropy rate preservation and higher order lumpability"
    - "information measures for deterministic input output systems"

Connected through hyperedge HE-4 (induced by source paper "on the information loss in memoryless systems the multivariate case"):
  with members:
    - "information loss in static nonlinearities"

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)