Heterogeneous probabilistic models for optimisation and modelling of evolving spiking neural networks
This thesis proposes a novel feature selection and classification method employing evolving spiking neural networks (eSNN) and evolutionary algorithms (EA). The method is named the Quantum-inspired Spiking Neural Network (QiSNN) framework. QiSNN represents an integrated wrapper approach. An evolutio...
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| Format: | Others |
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Auckland University of Technology,
2010-07-12T02:01:20Z.
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| Online Access: | Get fulltext |