Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition

Authors:
Simei Gomes Wysoski;Lubica Benuskova;Nikola Kasabov
Affiliations:
Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand
Venue:
Neural Information Processing
Year:
2008

Citing 8
Cited 1

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Abstract

The paper describes the integration of brain-inspired systems to perform audiovisual pattern recognition tasks. Individual sensory pathways as well as the integrative modules are implemented using a fast version of spiking neurons grouped in evolving spiking neural network (ESNN) architectures capable of lifelong adaptation. We design a new crossmodal integration system, where individual modalities can influence others before individual decisions are made, fact that resembles some characteristics of the biological brains. The system is applied to the person authentication problem. Preliminary results show that the integrated system can improve the accuracy in many operation points as well as it enables a range of multi-criteria optimizations.