Skip to main content
Go to the home page of the European Commission (opens in new window)
English English
CORDIS - EU research results
CORDIS
Content archived on 2024-05-30

Evolving Probabilistic Spiking Neural Networks for Spatio-Temporal Pattern Recognition

Objective

Spiking neural networks (SNN), considered the third generation of neural networks, are a promising paradigm for the creation of new intelligent ICT and for the study of the brain. This new generation computational models and systems are potentially capable of modelling complex information processes due to their ability to represent and integrate different information dimensions, such as time, space, frequency, phase, and to deal with large volumes of data in an adaptive, self-organising, self-learning way. The progress in this direction has been slow in the past, but now there are more opportunities for a progress to be made and this is the aim of the proposed project. The host organisation, the Institute of Neuro-Informatics (INI), Zurich, has been developing VLSI technologies for implementing SNNs for many years. As it has mainly focused on the hardware development aspects, it is still lacking a theoretical framework for configuring and applying VLSI SNNs to wider computational problems. The contribution of this project and of the incoming researcher Prof. Kasabov will be crucial for making a breakthrough in this domain. The project proposes to devise a theoretical framework and a methodology for the design of novel SNN, namely evolving probabilistic spiking neural networks (epSNN) and evolving probabilistic computational neuro-genetic models (epCNGM) along with their implementation on existing software and hardware platforms at the host organisation INI. The resulting technologies will offer a new way to efficiently solve a wide range of complex spatio-temporal pattern recognition problems, including: audio-visual pattern recognition; EEG brain data analysis; associative memories; neurogenetic cognitive systems. Further applications of the epCNGM are expected to be developed for modelling brain data related to neurodegenerative diseases, such as Alzheimer’s disease. Knowledge will be transferred from the visiting researcher Prof. Kasabov to INI and Europe.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

You need to log in or register to use this function

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

FP7-PEOPLE-2010-IIF
See other projects for this call

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MC-IIF - International Incoming Fellowships (IIF)

Coordinator

University of Zurich
EU contribution
€ 121 352,50
Address
RAMISTRASSE 71
8006 ZURICH
Switzerland

See on map

Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data
My booklet 0 0