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

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

85
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
85
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

62
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
62
Load-frequency control01:28

Load-frequency control

119
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
119
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

85
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
85
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

40
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...
40
Effects of feedback01:24

Effects of feedback

514
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
514

You might also read

Related Articles

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

Sort by
Same author

Resistin, an adipocytokine, offers protection against acute myocardial infarction.

Journal of molecular and cellular cardiology·2007
Same author

Liquid chromatographic analysis of phosphoamino acids at femtomole level using chemical derivatization with N-hydroxysuccinimidyl fluorescein-O-acetate.

Analytica chimica acta·2007
Same author

6-oxy-(acetyl piperazine) fluorescein as a new fluorescent labeling reagent for free fatty acids in serum using high-performance liquid chromatography.

Journal of chromatography. A·2007
Same author

Synthesis and fluorescence properties of 5,7-diphenylquinoline and 2,5,7-triphenylquinoline derived from m-terphenylamine.

Molecules (Basel, Switzerland)·2007
Same author

[Metabolic engineering of terpenoids in plants].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2007
Same author

Hedgehog signaling in the murine melanoma microenvironment.

Angiogenesis·2007

Related Experiment Video

Updated: Jun 3, 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

1.6K

Reduced Gaussian Kernel Filtered-x LMS Algorithm with Historical Error Correction for Nonlinear Active Noise Control.

Jinhua Ku1,2, Hongyu Han1,2, Weixi Zhou1,2

  • 1College of Computer Science, Sichuan Normal University, Chengdu 610101, China.

Entropy (Basel, Switzerland)
|January 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a reduced Gaussian kernel filtered-x least mean square (RGKxLMS) algorithm for nonlinear active noise control (NANC) systems. The new method offers reduced complexity and stable performance, enhancing noise reduction capabilities.

Keywords:
error-correction learningkernel filtered-x least mean square algorithmnonlinear active noise controlnonlinearity issues

More Related Videos

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

8.6K
X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells
00:10

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

13.7K

Related Experiment Videos

Last Updated: Jun 3, 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

1.6K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

8.6K
X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells
00:10

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

13.7K

Area of Science:

  • Signal Processing
  • Control Systems Engineering
  • Computational Mathematics

Background:

  • Traditional kernel filtered-x least mean square (KFxLMS) algorithms face computational and storage challenges in nonlinear active noise control (NANC).
  • Efficient algorithms are needed to improve the performance and practicality of NANC systems.

Purpose of the Study:

  • To introduce a computationally efficient Reduced Gaussian Kernel filtered-x Least Mean Square (RGKxLMS) algorithm for NANC systems.
  • To develop an enhanced algorithm, the Historical Error Correction RGKxLMS (HECRGKxLMS), for improved noise reduction.
  • To analyze the performance and stability of the proposed algorithms.

Main Methods:

  • Development of the RGKxLMS algorithm to reduce computational load compared to KFxLMS.
  • Introduction of the HECRGKxLMS algorithm by incorporating historical error information.
  • Analysis of mean weight behavior and computational complexity.
  • Validation using diverse noise types: Lorenz chaotic, non-stationary, and factory noise.

Main Results:

  • The RGKxLMS algorithm demonstrates reduced computational complexity and mean stable performance.
  • The HECRGKxLMS algorithm shows enhanced noise reduction capabilities.
  • Both proposed algorithms were validated effectively across various challenging noise environments.

Conclusions:

  • The RGKxLMS algorithm provides an efficient alternative for NANC systems, addressing limitations of traditional methods.
  • The HECRGKxLMS algorithm further improves noise cancellation performance.
  • The validated effectiveness confirms the potential of these algorithms in practical NANC applications.