human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Avoiding Saturation By Trajectory Reparameterization"
  Abstract: The problem of trajectory tracking in the presence of input constraints is considered. The desired trajectory is reparameterized on a slower time scale in order to avoid input saturation. Necessary conditions that the reparameterizing function must satisfy are derived. The deviation from the nominal trajectory is minimized by formulating the problem as an optimal control problem.

Connected through hyperedge HE-1 (induced by source paper "Global Stabilization of Linear Discrete-Time Systems with Bounded Feedback"):
  with members:
    - "New Characterizations of Input to State Stability"
    - "j"
    - "On Finite Gain Stabilizability of Linear Systems Subject to Input Saturation"
    - "STABILIZATION WITH SATURATED ACTUATORS, A WORKED EXAMPLE:F-8 LONGITUDINAL FLIGHT CONTROL"

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Neural_Networks