human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "PHONETIC CLASSIFICATION OF TIMIT SEGMENTS PREPROCESSED WITH LYON'S COCHLEAR MODEL USING A SUPERVISED/UNSUPERVISED HYBRID NEURAL NETWORK"):
  Abstract: We report results on vowel and stop consonant recognition with tokens extracted from the TIMIT database. Our current system differs from others doing similar tasks in that we do not use any specific time normalization techniques. We use a very detailed biologically motivated input representation of the speech tokens - Lyon's cochlear model as implemented by Slaney [20]. This detailed, high dimensional representation, known as a cochleagram, is classified by either a back-propagation or by a hybrid supervised/unsupervised neural network classifier. The hybrid network is composed of a biologically motivated unsupervised network and a supervised back-propagation network. This approach produces results comparable to those obtained by others without the addition of time normalization.

Includes members:
  Member "Objective Function Formulation of the BCM Theory of Visual Cortical Plasticity: Statistical Connections, Stability Conditions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Receptive Fields for Vision: from Hyperacuity to Object Recognition")
  Member "Feature Extraction Using an Unsupervised Neural Network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain")
  Member "Combining Exploratory Projection Pursuit And Projection Pursuit Regression With Application To Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Feature Extraction Using an Unsupervised Neural Network")
  Member "Face Recognition using a Hybrid Supervised/Unsupervised Neural Network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Multimodality Exploration in Training an Unsupervised Projection Pursuit Neural Network")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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