Mirko Sangiorgio
Implementation of an unsupervised fully-connected spiking neural network on SpiNNaker for pattern classification.
Rel. Massimo Ruo Roch, Guido Pagana, Mauricio Perez, Robin Augustine. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2022
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Abstract
Machine Learning (ML) is an application of Artificial Intelligence based on the concept that machines should be given access to data and learn specific tasks by themselves, without being explicitly programmed. Artificial Neural Networks (ANNs) are a special type of ML algorithms inspired by the human brain and its functioning is similar to the way neurons work in our system. That is, just like how the neurons can learn from the past data, similarly, the ANN, in order to mimic the behavior of the biological neural networks, learn from the data and provide responses in the form of predictions or classifications.
The third generation on neural networks, called Spiking Neural Networks, represents a new computation theory that mimics the brain working principles better than traditional artificial neural networks
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