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: "Complete Controllability of Continuous-Time Recurrent Neural Networks"
  Abstract: This paper presents a characterization of controllability for the class of control systems commonly called (continuous-time) recurrent neural networks. The characterization involves a simple condition on the input matrix, and is proved when the activation function is the hyperbolic tangent.

Connected through hyperedge HE-1 (induced by source paper "Recurrent Neural Networks: Some Systems-Theoretic Aspects"):
  with members:
    - "NEURAL NETS AS SYSTEMS MODELS AND CONTROLLERS suitability of "neural nets" as models for dynamical"
    - "NETWORKS, FUNCTION DETERMINES FORM"
    - "OBSERVABILITY IN RECURRENT NEURAL NETWORKS"

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