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

Fisher's Exact Test01:08

Fisher's Exact Test

1.5K
Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
1.5K
Methods of Medium Optimization01:28

Methods of Medium Optimization

63
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
63
Optimal Foraging00:48

Optimal Foraging

14.4K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
14.4K
Behrens–Fisher Test00:57

Behrens–Fisher Test

340
The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test...
340
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

887
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
887
Poisson Probability Distribution01:09

Poisson Probability Distribution

12.6K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
12.6K

You might also read

Related Articles

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

Sort by
Same author

Quantitative assessment of dynamic movement reveals deficits due to hemiparetic stroke.

Journal of neuroengineering and rehabilitation·2025
Same author

Characterizing eye gaze and mental workload for assistive device control.

Wearable technologies·2025
Same author

Collaborative robots can augment human cognition in regret-sensitive tasks.

PNAS nexus·2024
Same author

Affordances for throwing: An uncontrolled manifold analysis.

PloS one·2024
Same author

Reduced learning rates but successful learning of a coordinated rhythmic movement by older adults.

Quarterly journal of experimental psychology (2006)·2024
Same author

Characterizing Eye Gaze for Assistive Device Control.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2023

Related Experiment Video

Updated: Apr 18, 2026

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
09:32

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

9.9K

Trajectory Synthesis for Fisher Information Maximization.

Andrew D Wilson1, Jarvis A Schultz1, Todd D Murphey1

  • 1Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208 USA.

IEEE Transactions on Robotics : a Publication of the IEEE Robotics and Automation Society
|January 20, 2015
PubMed
Summary

Optimizing experimental trajectories enhances dynamic system model parameter estimation. This method improves Fisher information matrix norms, significantly reducing parameter estimate errors in real-world applications.

Keywords:
Maximum likelihood estimationoptimal controlparameter estimation

More Related Videos

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.1K
Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
10:56

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

13.1K

Related Experiment Videos

Last Updated: Apr 18, 2026

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
09:32

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

9.9K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.1K
Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
10:56

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

13.1K

Area of Science:

  • Dynamic Systems and Control
  • Parameter Estimation
  • Experimental Design

Background:

  • Accurate model parameter estimation is crucial for dynamic systems.
  • Globally optimal trajectory design is often infeasible for nonlinear systems.
  • Measurement noise complicates parameter estimation.

Purpose of the Study:

  • To develop a continuous-time optimization method for locally optimal experimental trajectories.
  • To improve parameter estimation accuracy in dynamic systems with measurement noise.
  • To enhance the Fisher Information Matrix (FIM) norm via trajectory optimization.

Main Methods:

  • Formulated a continuous-time optimization algorithm to find trajectories that maximize a norm of the Fisher Information Matrix (FIM).
  • Utilized a double-pendulum cart apparatus for numerical and experimental validation.
  • Compared optimized trajectories against initial trajectories in simulations and experiments.

Main Results:

  • Optimized trajectories increased the minimum eigenvalue of the FIM by three orders of magnitude in simulations.
  • Experimental validation demonstrated an order-of-magnitude improvement in parameter estimate error.
  • The method provides a practical approach to enhance parameter estimation through trajectory optimization.

Conclusions:

  • The proposed continuous-time optimization method effectively generates locally optimal trajectories for parameter estimation.
  • This approach significantly improves the quality of parameter estimates in dynamic systems, even with measurement noise.
  • The technique offers a practical and validated strategy for enhancing experimental design in dynamic system modeling.