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 Experiment Videos

System identification from multiple short-time-duration signals.

Sean R Anderson1, Paul Dean, Visakan Kadirkamanathan

  • 1Neural Algorithms Research Group, Department of Psychology, University of Sheffield, Western Bank, Sheffield S10 2TP, U.K. s.anderson@sheffield.ac.uk

IEEE Transactions on Bio-Medical Engineering
|December 14, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Pathways and pitfalls: a qualitative study of student experiences in biomedical science education.

FEBS open bio·2026
Same author

The balance between defence systems and horizontal gene transfer shapes adaptation in clinical strains of Acinetobacter spp.

Journal of applied microbiology·2026
Same author

Microbial community dynamics over large spatial and environmental gradients in a subtropical ocean basin.

Applied and environmental microbiology·2026
Same author

Asymmetric temporal envelope encoding: Lateralization with varying envelope shape and spectral mismatch.

The Journal of the Acoustical Society of America·2025
Same author

SemaNet: Bridging Words and Numbers for Predicting Missing Environmental Data in Life Cycle Assessment.

Environmental science & technology·2025
Same author

Quantifying the local strain energy density distribution in the mouse tibia: the critical role of the loading direction.

Biomechanics and modeling in mechanobiology·2025
Same journal

Enhancing Volumetric Imaging in Linear-Array Photoacoustic Tomography: multiview fusion with deep learning.

IEEE transactions on bio-medical engineering·2026
Same journal

Robust Rule-based Heuristic Assistance Strategy for a Semi-Active Shoulder Exoskeleton Used in Overhead Work.

IEEE transactions on bio-medical engineering·2026
Same journal

Highly Accelerated 1-mm Isotropic 3D Chemical Exchange Saturation Transfer MRI Using Wave-Co-CAIPI at 5 Tesla.

IEEE transactions on bio-medical engineering·2026
Same journal

Systematic Evaluation of Hip Exoskeleton Assistance Parameters for Enhancing Gait Stability During Ground Slip Perturbations.

IEEE transactions on bio-medical engineering·2026
Same journal

SleepConFormer: A Single-Channel EEG Framework for Sleep Staging and Consciousness Assessment in Patients with Disorders of Consciousness.

IEEE transactions on bio-medical engineering·2026
Same journal

Modeling Partial and Total Support of Left Ventricular Assist Device for Discrete Hemodynamic Control Framework.

IEEE transactions on bio-medical engineering·2026
See all related articles

This study introduces a new system identification algorithm for parameter estimation using multiple short signals. The method improves accuracy by minimizing prediction error and avoids biased estimates common with least squares in noisy data.

Area of Science:

  • Engineering
  • Control Systems
  • Biomedical Engineering

Background:

  • System identification often relies on limited, short-duration signal data.
  • Existing methods like least squares can produce biased estimates with noisy signals.

Purpose of the Study:

  • Develop a robust system identification algorithm for short-time signals.
  • Improve parameter estimation accuracy in the presence of measurement noise.

Main Methods:

  • Parameter estimation via minimizing simulated prediction error across multiple signals.
  • Algorithm designed to exclude the estimation of initial states for each signal.

Main Results:

  • Proposed algorithm demonstrates superior performance compared to the least squares method.

Related Experiment Videos

  • Numerical simulations confirm the algorithm's effectiveness with noisy data.

    • Conclusions:

    • The developed algorithm offers a reliable approach for system identification with multiple short signals.
    • Successfully applied to identify parameters of the passive oculomotor plant, characterizing its visco-elastic properties.