Sequential learning neural network for sonar target differentiation

In this paper, we investigate the use of neural networks in processing the sonar signals reflected by different targets and localization applications for indoor environments. It describes how the newly developed MRAN algorithm performs on pattern classification of various targets and a comparison between its performance and probabilistic neural network (PNN). The robustness and plasticity of the MRAN neural network performance are tested and compared.