Codes to simulate wavefront shaping experiments and optimally recover the transfer matrix of dynamic scattering media in an online and recursive fashion.
Its use in a conventional wavefront shaping experiment is illustrated in the figure below.
The core of the process lies in the so-called Recursive Least-Squares (RLS) algorithm, described in pseudo-code below.
Please find more information in our accompanying paper, "Online learning of the transfer matrix of dynamic scattering media: wavefront shaping meets multidimensional time series".
- main_function.m : simulates wavefront shaping experiments at varying stability times of the scattering medium and noise levels, and produces figures comparing a conventional transfer-matrix approach with the one based on the RLS algorithm;
- TM.m : reconstructs the transfer matrix using a conventional algorithm employing N measurements, where N is the number of inputs degrees of freedom;
- RLS_TM.m : reconstructs the transfer matrix based on the RLS algorithm;
- RLS_update.m : the updating routine of the RLS algorithm, as described in the figure above;
- error_compute.m : computes the root-mean-square normalized error between the ground truth transfer matrix and its estimate.
You may expect results to look like the figure below.
