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 "NEURAL NETWORK APPROACH TO BLIND SEPARATION AND ENHANCEMENT OF IMAGES"):
  Abstract: In this contribution we propose a new solution for the problem of blind separation of sources (for one dimensional signals and images) in the case that not only the waveform of sources is unknown, but also their number. For this purpose multi-layer neural networks with associated adaptive learning algorithms are developed. The primary source signals can have any non-Gaussian distribution, i.e. they can be sub-Gaussian and/or super-Gaussian. Computer experiments are presented which demonstrate the validity and high performance of the proposed approach.

Includes members:
  Member "SELF-ADAPTIVE NEURAL NETWORKS FOR BLIND SEPARATION OF SOURCES":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "A New Learning Algorithm for Blind Signal Separation")
  Member "A New Learning Algorithm for Blind Signal Separation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Independent Component Analysis by General Non-linear Hebbian-like Learning Rules")
  Member "Equivariant adaptive source separation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "A New Learning Algorithm for Blind Signal Separation")

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