Embedded Spiking Neural Network

Provided by: International Journal of Engineering and Advanced Technology (IJEAT)
Topic: Networking
Format: PDF
Neural networks are computational models of the brain. These networks are excellent at solving problems for which a solution seems easy to obtain for the brain, but requires a lot of efforts using standard algorithmic techniques. Examples of such problems are pattern recognition, perception, generalization and non-linear control. In the brain, all communication between neurons occur using action potentials or spikes. In classical neural models these individual spikes are averaged out in time and all interaction is identified by the mean firing rate of the neurons.

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