[Talks@IDSIA] TALK: Wednesday, Jan 28, h. 11:00 -
Maurizio Fiasché, On the use of Quantum inspired Spiking
Neural Networks and on their integration with chaotic
measurements on EEG data for modelling epileptic brain
On the use of Quantum inspired Spiking Neural Networks and on
their integration with chaotic measurements on EEG data for
modelling epileptic brain
Abstract.
In the last 20 years a lot of works in literature analysed and
proposed several methods capable to predict the occurrence of
seizures from the electroencephalogram (EEG) of epilepsy patients.
In spite of promising results presented, more recent evaluations
could not reproduce these optimistic findings. This evaluation
poses again the issue of the EEG of epileptic patients used for
the prediction of seizures used in a joint way with other data
(e.g. fMRI). Spatio- and spectro-temporal brain data (STBD) are
the most commonly collected data for measuring brain response to
external stimuli or to internal events such as epileptic seizures.
Spiking neural networks (SNN) are brain-like connectionist
methods, where the output activation function is represented as a
train of spikes and not as a potential. This and other reasons do
SNN models more biologically close to brain principles than any of
the previous Artificial Neural Networks (ANN) methods, and for
this reason, are presented as the third generation of ANN. In
fact, they have great potential for solving complicated
time-dependent pattern recognition problems defined by time series
and STBD because of their inherent dynamical representation.
Nevertheless several challenges have been reported in works in
literature for SNN techniques studied. In this presentation we
want to present a particular type of SNN, the evolving SNN (eSNN)
with a Quantum inspired evolutionary technique for its weights,
parameters and features optimization. In fact, the first challenge
approached in in this presentation is the feature and parameter
optimization in a SNN. A QiEA is a novel type of quantum-inspired
evolutionary algorithm (QiEA) for feature and parameter
optimization used here in a SNN. The QiEA is inspired by the
multiple universes principle of quantum computing, such as a
quantum bit and superposition of states. QiEA represents the most
recent advance in the field of evolutionary computation thus, as
second objective, the architecture of a QiESNN is presented here
and proposed for pattern recognition on temporal brain data.
The third objective is about the presentation of a framework where
Chaotic measurement and the QiESNN presented before are used in an
integrated way for better understanding the epileptic brain. This
framework concept, architecture and applications are approached
with several possible future evolutions.
Maurizio Fiasché is research coordinator at the Department of
Economics, Management and Industrial Engineering of Politecnico di
Milano (POLIMI), where his research interests are in Computational
Intelligence and ICT for manufacturing. He received a Ph.D. in
Computer Engineering in 2010 and a M.Sc. in Electronical
Engineering with magna cum laude in 2006 at University of Reggio
Calabria, Italy. Member of INNS and Senior Member of IEEE in:
Computational Intelligence, EMB, Signal Processing and Computer
societies, He was involved in two IEEE WGs as member for his
expertise: IEEE P23026™ Standard for Systems and software
engineering – Engineering and management of websites for systems,
software, and services information, and IEEE P2145-1™ : Standard
for Smart Transducer Interface for Sensors and Actuators - Common
Network Services. He won a best paper award during ICONIP 2008
conference in Auckland, NZ. He is author of 37 papers in
international journals and conference proceedings, member in
Technical Program committee in about 50 International Conferences,
and referee for top international Journal also including Elsevier
Neural Networks, Neural Computing and IEEE Transactions. He has
been involved as Senior Researcher in Social&Smart EU FP7
(FIRE Project) with University of Milan, in white’R FP7 Project,
and in Touchplant Project of Regione Lombardia with Politecnico di
Milano. Moreover he has been lecture for several Universities and
Institutes in Electrotechnical, Statistical Inference, Computer
Science and Signal Processing courses. He is also senior
consultant as ICT Project Manager and Software Engineer for
several national and multinational Companies and consulting Groups
since 14 years.