Automatic Classification using Self-Organising Neural Networks in Astrophysical Experiments

摘要: Self-Organising Maps (SOMs) are effective tools in classification problems, and recent years the even more powerful Dynamic Growing Neural Networks, a variant of SOMs, have been developed. Automatic Classification (also called clustering) is an important difficult problem many Astrophysical experiments, for instance, Gamma Ray Burst classification, or gamma-hadron separation. After brief introduction to problem, we discuss section 2. Section 3 discusses with various models growing neural networks finally 4 research perspectives efficient astrophysical problems.