Schemata, Distributions and Graphical Models in Evolutionary Optimization
Journal of Heuristics
Extending Population-Based Incremental Learning to Continuous Search Spaces
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Telephone Network Traffic Overloading Diagnosis and Evolutionary Computation Techniques
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift
Evolutionary Computation
Neural associative memory for brain modeling and information retrieval
Information Processing Letters - Special issue on applications of spiking neural networks
Finding iterative roots with a spiking neural network
Information Processing Letters - Special issue on applications of spiking neural networks
Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing)
Evolving Connectionist Systems: The Knowledge Engineering Approach
Evolving Connectionist Systems: The Knowledge Engineering Approach
Computational Neurogenetic Modeling
Computational Neurogenetic Modeling
Natural Computing: an international journal
Normalized mutual information feature selection
IEEE Transactions on Neural Networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Evolving Intelligence in Humans and Machines: Integrative Evolving Connectionist Systems Approach
IEEE Computational Intelligence Magazine
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
Real-Valued Compact Genetic Algorithms for Embedded Microcontroller Optimization
IEEE Transactions on Evolutionary Computation
Simple model of spiking neurons
IEEE Transactions on Neural Networks
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Towards spatio-temporal pattern recognition using evolving spiking neural networks
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Reservoir-based evolving spiking neural network for spatio-temporal pattern recognition
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
NeuCube evospike architecture for spatio-temporal modelling and pattern recognition of brain signals
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
A target-reaching controller for mobile robots using spiking neural networks
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
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This study introduces a quantum-inspired spiking neural network (QiSNN) as an integrated connectionist system, in which the features and parameters of an evolving spiking neural network are optimized together with the use of a quantum-inspired evolutionary algorithm. We propose here a novel optimization method that uses different representations to explore the two search spaces: A binary representation for optimizing feature subsets and a continuous representation for evolving appropriate real-valued configurations of the spiking network. The properties and characteristics of the improved framework are studied on two different synthetic benchmark datasets. Results are compared to traditional methods, namely a multi-layer-perceptron and a naive Bayesian classifier (NBC). A previously used real world ecological dataset on invasive species establishment prediction is revisited and new results are obtained and analyzed by an ecological expert. The proposed method results in a much faster convergence to an optimal solution (or a close to it), in a better accuracy, and in a more informative set of features selected.