Speed Thrills With Neural Networks

Software and hardware-based neural network-based techniques are being successfully applied to engine control and diagnostics in automotive embedded systems.  Taking them further, Steve Furber, ICL Professor of Computer Engineering at Manchester University, is planning to model various ways in which neurons may express information in their patterns of spikes, based on the assumption that populations of neurons producing firing patterns have a very high information capacity, based on the dynamic behaviour of the spikes.  The promise is an alternative computational architecture that can outperform our fastest systems in tasks such as face recognition, speech processing, and the use of natural language.

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