We propose a novel control approach that combines offline supervised learning to address
the challenges posed by non-linear phase reconstruction using unmodulated pyramid …

Correction performance of an adaptive optics (AO) system is severely limited by its system
latency under high temporal frequency distortions. Wavefront prediction methods has been …

Advances in the field of deep learning have motivated a flurry of research into the
application of neural networks to wavefront sensing for adaptive optics. This paper gives an …

The time-delay problem, which is introduced by the response time of hardware for
correction, is a critical and non-ignorable problem of adaptive optics (AO) systems. It will …

Adaptive Optics (AO) technology is an effective means to compensate for wavefront
distortion, but its inherent delay error will cause the compensation wavefront on the …

Adaptive optics (AO) has great applications in many fields and has attracted wide attention
from researchers. However, both traditional and deep learning-based AO methods have …

In order to improve the image detail restoration effect of online education videos and
improve the quality of online education images, a method for image detail restoration of …

Atmospheric turbulence and obstacles can distort rays during transmission, resulting in
significant wavefront distortion and loss of optical field information. This paper employs the …

Adaptive optics (AO) technology is an effective means to compensate for atmospheric
turbulence, but the inherent delay error of an AO system will cause the compensation phase …

Free space optical communication has become increasingly popular in the past decade due
to its terahertz bandwidth, unlicensed spectrum, and enhanced security features. This …