Hsu, R.C. and Alexander, S.S. (1993) Recognition of earthquakes and explosions using a data compression neural network. Proceedings of the 1993 IEEE-SP Workshop, Neural Networks for Processing  III, 6-9 September 1993, 421-430.
区分天然地震和人工爆炸的可视化方法Visualization Methods for Discriminating between Earthquakes and Explosions
田野, 黄汉明, 边银菊, 赵晨杰
震源类型, 可视化, 对称点模式, 天然地震, 人工爆炸Seismic Source Type, Visualization, Symmetric Dot Pattern (SDP), Earthquake, Explosion
《Advances in Geosciences》, Vol.4 No.3, 2014-06-17
Seismic signals classification and discrimination between earthquakes and explosions are essential technology for implementation of the comprehensive nuclear test ban treaty (CTBT) and also are very important for keeping national security and world peace. Since 1959, this task has continuously been a hot spot and a hard problem of seismological researches. Based on the principles of scientific data visualization, using novel aesthetic graphics to reveal a lot of useful information contained in the data, this paper makes an attempt to put forward a kind of integrative visualization method for an event—earthquake or explosion with multi-observatories data in different locations. The method is to draw many intuitive graphics in a compact and integrative array form for each event in order to visually and conveniently distinguish earthquakes and explosions. Each picture in the graphical array for an event is drawn by an implementation of Symmetric Dot Pattern (SDP) for a seismic signal from a channel of an observatory. Totally 35 earthquake events and 27 explosion events are considered and drawn into arrays of SDP. These pictorial arrays of SDP show considerably significant differences between earthquakes and explosions. This provides a new potential measure to rapidly (can be less than 5 minutes) recognize the seismic source type— explosion or earthquake, whenever the seismic signal has been observed and prepared.