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This paper proposes a novel method for optimizing features and parameters in the Evolving Spiking Neural Network (ESNN) using Quantum-inspired Particle Swarm Optimization (QiPSO). This study reveals the interesting concept of QiPSO in which information is represented as binary structures. The mechanism simultaneously optimizes the ESNN parameters and relevant features using wrapper approach. A synthetic...
Despite a variety of artificial neural network (ANN) categories, backpropagation network (BP) and Elman recurrent network (ERN) are the widespread modus operandi in real applications. However, there are many drawbacks in BP network, for instance, confinement in finding local minimum and may get stuck at regions of a search space or trap in local minima. To solve these problems, various optimization...
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