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: "a differential lyapunov framework for contraction analysis"
  Abstract: Lyapunov's second theorem is an essential tool for stability analysis of differential equations. The paper provides an analog theorem for incremental stability analysis by lifting the Lyapunov function to the tangent bundle. The Lyapunov function endows the state-space with a Finsler structure. Incremental stability is inferred from infinitesimal contraction of the Finsler metrics through integration along solutions curves.

Connected through hyperedge HE-1 (induced by source paper "contracting implicit recurrent neural networks stable models with improved trainability"):
  with members:
    - "specialized interior point algorithm for stable nonlinear system identification"
    - "stabilizing gradients for deep neural networks via efficient svd parameterization"
    - "stable recurrent models"
    - "convex parameterizations and fidelity bounds for nonlinear identification and reduced order modelling"
    - "efficient orthogonal parametrisation of recurrent neural networks using householder reflections"
    - "a simple way to initialize recurrent networks of rectified linear units"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"
    - "on the difficulty of training recurrent neural networks"

Connected through hyperedge HE-2 (induced by source paper "krasovskii s passivity"):
  with members:
    - "differentiation and passivity for control of brayton moser systems"
    - "differential passivity like properties for a class of nonlinear systems"
    - "on differential passivity of physical systems"

Connected through hyperedge HE-3 (induced by source paper "robust contraction analysis of nonlinear systems via differential iqc"):
  with members:
    - "contraction analysis of switched systems via regularization"
    - "control contraction metrics convex and intrinsic criteria for nonlinear feedback design"
    - "on differentially dissipative dynamical systems"

Connected through hyperedge HE-4 (induced by source paper "control contraction metrics on finsler manifolds"):
  with members:
    - "on existence of separable contraction metrics for monotone nonlinear systems"
    - "contraction analysis of switched systems via regularization"
    - "nonlinear stabilization via control contraction metrics a pseudospectral approach for computing geodesics"
    - "control contraction metrics convex and intrinsic criteria for nonlinear feedback design"
    - "logarithmic lipschitz norms and diffusion induced instability"

Connected through hyperedge HE-5 (induced by source paper "differentially passive circuits that switch and oscillate"):
  with members:
    - "dominance analysis of linear complementarity systems"
    - "analysis of lur e dominant systems in the frequency domain"
    - "a dissipativity theorem for p dominant systems"
    - "on differentially dissipative dynamical systems"

Connected through hyperedge HE-6 (induced by source paper "distributed nonlinear control design using separable control contraction metrics"):
  with members:
    - "on existence of separable contraction metrics for monotone nonlinear systems"
    - "separability of lyapunov functions for contractive monotone systems"
    - "control contraction metrics convex and intrinsic criteria for nonlinear feedback design"

Connected through hyperedge HE-7 (induced by source paper "dominance analysis of linear complementarity systems"):
  with members:
    - "a dissipativity theorem for p dominant systems"

Connected through hyperedge HE-8 (induced by source paper "differential passivity like properties for a class of nonlinear systems"):
  with members:
    - "on differential passivity of physical systems"

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)