Spiking Neural Networks for Deep Learning and Knowledge Representation: Theory, Methods, and Applications

  in Special Issue   Posted on December 22, 2018

Information for the Special Issue

Submission Deadline: Thu 31 Jan 2019
Journal Impact Factor : 3.317
Journal Name : Neurocomputing
Journal Publisher:
Website for the Special Issue: https://www.journals.elsevier.com/neural-networks/call-for-papers/spiking-neural-networks-for-deep-learning-and-knowledge-repr
Journal & Submission Website: https://www.journals.elsevier.com/neurocomputing

Special Issue Call for Papers:

Learning algorithms for SNN, including Deep Learning
Theory of SNN
New information theories based on spike information representation
Big data and stream data processing in SNN
SNN model visualisation for the sake of model and data understanding
Neuromorphic hardware systems and applications
Optimization of SNN
SNN models of cognitive development
SNN for brain-inspired artificial intelligence
Knowledge transfer between humans and spiking neural network machines
SNN applications in neuroinformatics, bioinformatics, medicine and ecology.
SNN in BCI and neuro-robotics
Ensembles of self-organised SNN machines

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