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: "when do trajectories have bounded sensitivity to cumulative perturbations"
  Abstract: A dynamical system is said to have bounded sensitivity if an additive disturbance leads to a change in the state trajectory that is bounded by a constant multiple of the size of the cumulative disturbance. It was shown in Sharifnassab, et al. (2019) that the (negative) (sub)gradient field of a piecewise constant and convex function with finitely many pieces has always bounded sensitivity. In this paper, we investigate sensitivity of some generalizations of this class of systems, as well as other classes of practical interest. In particular, we show that the result in Sharifnassab, et al. (2019) does not generalize to the (negative) gradient field of a convex function. More concretely, we provide examples of gradient field of a twice continuously differentiable convex function, and subgradient field of a piecewise constant convex function with infinitely many pieces, that have unbounded sensitivity. Moreover, we give a necessary and sufficient condition for a linear dynamical system to have bounded sensitivity, in terms of the spectrum of the underlying matrix. The proofs and the development of our examples involve some intermediate results concerning transformations of dynamical systems, which are also of independent interest. More specifically, we study some transformations that when applied on a dynamical system with bounded sensitivity, preserve the bounded sensitivity property. These transformations include discretization of time and spreading of a system; a transformation that captures approximate solutions of the original system in a certain sense.

Connected through hyperedge HE-1 (induced by source paper "sensitivity to cumulative perturbations for a class of piecewise constant hybrid systems"):
  with members:
    - "nonexpansive piecewise constant hybrid systems are conservative"
    - "fluctuation bounds for the max weight policy with applications to state space collapse"
    - "cone schedules for processing systems in fluctuating environments"

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.SY(Systems and Control)