Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91352
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Title: Dynamic mutation enhanced particle swarm optimization for optical wavefront shaping
Authors: Woo, CM 
Li, H 
Zhao, Q 
Lai, P 
Issue Date: Jun-2021
Source: Optics express, 7 June 2021, v. 29, no. 12, p. 18420-18426
Abstract: Particle swarm optimization (PSO) is a well-known iterative algorithm commonly adopted in wavefront shaping for focusing light through or inside scattering media. The performance is, however, limited by premature convergence in an unstable environment. Therefore, we aim to solve this problem and enhance the focusing performance by adding a dynamic mutation operation into the plain PSO. With dynamic mutation, the "particles,"or the optimized masks, are mutated with quantifiable discrepancy between the current and theoretical optimal solution, i.e., the "error rate."Gauged by that, the diversity of the "particles"is effectively expanded, and the adaptability of the algorithm to noise and instability is significantly promoted, yielding optimization approaching the theoretical optimum. The simulation and experimental results show that PSO with dynamic mutation demonstrates considerably better performance than PSO without mutation or with a constant mutation, especially under a noisy environment.
Publisher: Optical Society of America
Journal: Optics express 
EISSN: 1094-4087
DOI: 10.1364/OE.425615
Rights: © 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement (https://www.osapublishing.org/library/license_v1.cfm#VOR-OA)
Journal © 2021
© 2021 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.
The following publication Woo, C. M., Li, H., Zhao, Q., & Lai, P. (2021). Dynamic mutation enhanced particle swarm optimization for optical wavefront shaping. Optics Express, 29(12), 18420-18426 is available at https://doi.org/10.1364/OE.425615
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