Abstract
Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a quantum-inspired version of the particle swarm optimization (PSO) algorithm, which outperforms traditional PSOs in search ability as well as having less parameter to control. In this paper, QPSO technique is introduced into BP neural network to instead adopting gradient descent method in BP learning algorithm. Due to the characteristic of the QPSO algorithm, the problems of traditional BPNN can be avoided, such as easily converging to local minimum. Then we adopt the new learning algorithm to training a neural network for face detection, and the experiment results testify its efficiency in this.
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Li, S., Wang, R., Hu, W., Sun, J. (2007). A New QPSO Based BP Neural Network for Face Detection. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_40
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DOI: https://doi.org/10.1007/978-3-540-71441-5_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71440-8
Online ISBN: 978-3-540-71441-5
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