“Predictive data modeling of large and fast streams of spatio/spectro temporal data using neuromorphic computation”

Presenters:  N.Kasabov, R.Pears, R.Hartono, KEDRI/AUT

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The talk presents first the main principles of neuromorphic computation and spiking neural networks (SNN), before it introduces the NeuCube  SNN architecture developed at KEDRI (www.kedri.aut.ac.nz). A methodology of using NeuCube for  predictive data modelling of large and fast streams of data is presented and demonstrated on a small scale example.

The implementation of NeuCube-based models on the high performance SNN platform SpiNNaker, of millions of processing elements, developed at the University of Manchester is discussed. Future work of exploring NeuCube/SpiNNaker models and systems for SKA data is discussed.

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Professor Nikola Kasabov – bio

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