Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Analytical framework for guide-star arrangement optimization in solar ground-layer adaptive optics.

Optics letters·2026
Same author

Dispersed fringe cophasing method based on principal component analysis: erratum.

Optics letters·2025
Same author

Corrected field-of-view estimation for ground-based telescopes in multi-conjugate adaptive optics based on non-conjugate correction analysis of deformable mirrors.

Optics express·2025
Same author

Optimal gain integral control based on a fractional-order delayed observer in adaptive optics.

Optics express·2025
Same author

Lensless extended depth of field imaging using PSF correction and pre-denoising.

Optics express·2025
Same author

Nondeterministic wavefront estimation based on deep learning for multi-band synchronous high-resolution reconstruction technology.

Optics express·2025
See all related articles

Related Experiment Video

Updated: Jun 5, 2026

Bringing the Visible Universe into Focus with Robo-AO
10:35

Bringing the Visible Universe into Focus with Robo-AO

Published on: February 12, 2013

Wavefront sensorless adaptive optics: a general model-based approach.

Huang Linhai1, Changhui Rao

  • 1The Laboratory on Adaptive Optics, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China. hlhjs@163.com

Optics Express
|January 26, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient model-based correction method for wavefront sensorless adaptive optics (AO) systems. The new approach significantly improves aberration correction using fewer measurements, enhancing system performance.

More Related Videos

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter
05:14

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter

Published on: September 16, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Related Experiment Videos

Last Updated: Jun 5, 2026

Bringing the Visible Universe into Focus with Robo-AO
10:35

Bringing the Visible Universe into Focus with Robo-AO

Published on: February 12, 2013

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter
05:14

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter

Published on: September 16, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Area of Science:

  • Optics and Photonics
  • Adaptive Optics
  • Image Processing

Background:

  • Wavefront sensorless adaptive optics (AO) systems are crucial for optimizing optical performance.
  • Efficient aberration correction methods are essential for achieving optimal results in AO systems.
  • Existing methods may require numerous measurements, limiting efficiency.

Purpose of the Study:

  • To present a general model-based correction method for wavefront sensorless AO systems.
  • To demonstrate an efficient approach for aberration correction with reduced measurements.
  • To validate the proposed method through numerical simulations.

Main Methods:

  • Developed a general model-based correction approach utilizing the relationship between wavefront gradients' second moments and far-field intensity distribution's FWHM.
  • Incorporated predetermined bias functions (common sets of functions) into the model.
  • Performed numerical simulations to correct various random aberrations.

Main Results:

  • The model-based method effectively corrects aberrations using significantly fewer photodetector measurements (N+1 for N aberration modes).
  • Achieved a substantial improvement in the Strehl ratio, increasing from 0.07 to approximately 0.90.
  • Demonstrated the method's capability with diverse random aberrations.

Conclusions:

  • The presented general model-based correction method offers an efficient solution for wavefront sensorless AO systems.
  • The approach reduces the number of required photodetector measurements while achieving high-quality aberration correction.
  • This method holds promise for advancing the performance and practicality of adaptive optics applications.