“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


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.


Professor Nikola Kasabov – bio