Wheeled Vehicles Classification Using Radial Base Function Neural Network - Intelligent Control Systems and Optimization

The paper presents the problem of using neural network for military vehicle classification on the basis of ground vibration. One of the main element of the system is a unit called geophone. This unit allows to measure amplitude of ground vibration in each direction for certain period of time. The value of amplitude is used to fix the characteristic frequencies of each vehicle. If we want to fix the main frequency it is necessary to use Fourier transform. In this case the fast Fourier transform FFT was used. Because the neural network (Radial Basis Function network) was used, the learning set has to be prepared. Please find attached the results of using RBF neural network such as: example of learning, validation and test sets, structure of the networks and learning algorithm, learning and testing results.