Application Of Temporal Neural Networks To Source Localisation

In this paper, we present several neural networks approaches to deal with the problem of source localisation in signal processing. To locate a far field source, we have to retrieve the propagation delays between sensors. They are the only relevant temporal information we can handle on the signal. As we have to process temporal data, we study different time representations in neural networks. First, time may be represented explicitly and externally with multilayer perceptrons. Then, we use a time-delay neural network that appears to be more suitable to represent explicitly the temporal nature of the signal. Last, we study recurrent neural networks that represent time in their internal organisation. 1. Introduction Neural Networks (NNs) have been successfully applied in many domains. In some cases, they must take temporal information into account like in speech recognition or signal processing. But it is not always easy to represent temporal data, especially when they simultaneously co..