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: "Observability of Linear Systems with Saturated Outputs"
  Abstract: In this paper, we present necessary and sufficient conditions for observability of the class of output-saturated systems. These are linear systems whose output passes through a saturation function before it can be measured.

Connected through hyperedge HE-1 (induced by source paper "LINEAR SYSTEMS WITH SIGN-OBSERVATIONS"):
  with members:
    - "Sample Complexity for Learning Recurrent Perceptron Mappings"
    - "Interconnected Automata and Linear Systems: A Theoretical Framework in Discrete-Time In Hybrid Systems III: Verification"
    - "BACKPROPAGATION SEPARATES WHERE PERCEPTRONS DO"
    - "Lemma 2.3 The system is reachable and observable and realizes the same input/output behavior as"

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