Integration of genetic and bat algorithms towards a parameter-free optimization scheme in iterative wavefront shaping
Qi Zhao, Chi Man Woo, Huanhao Li, Tianting Zhong, Zhipeng Yu, Puxiang Lai
Puxiang Lai* (Department of Biomedical Engineering, Hong Kong Polytechnic University) puxiang.lai@polyu.edu.hk
In this work, we proposed a parameter-free algorithm (PFA) for iterative wavefront shaping, in which the time-consuming parameter tuning process is not required. The simulation and experiment results show that PFA can achieve better performance than GA and BA, without a parameter tuning process. Furthermore, since the mutation rate in PFA is inherited from the dynamic mutation algorithm, which has demonstrated high adaptability against perturbations, the robustness of PFA is satisfactory. In the future, a field-programmable gate array (FPGA) based system can be implemented to accelerate iterative wavefront shaping and achieve real-time optical focusing in dynamic scattering media, such as biological tissue.
