Dynamic quantum-inspired particle swarm optimization as feature and parameter optimizer for evolving spiking neural networks
This paper proposes a new structure for Quantum-inspired Particle Swarm Optimization (QiPSO) to enhance feature and parameter optimization of Evolving Spiking Neural Networks (ESNN). The new Dynamic Quantum-inspired Particle Swarm Optimization (DQiPSO) will be integrated within ESNN where features a...
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International Association of Computer Science and Information Technology Press (IACSIT Press)
2012
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