Classifying seismic signals via RCE neural network

A discussion is presented of the use of a restricted coulomb energy (RCE) neural network to perform target recognition based on seismic signals. The training and testing patterns are the seismic signals of helicopters, tracked vehicles, and wheeled vehicles. It is found that the medium- and high-frequency parts of the seismic signal carry critical information for target recognition. A contrast-enhancement technique is applied to the medium- and high-frequency parts of the power spectrum to improve the performance of the system