Jove
Visualize
Contact Us

Related Concept Videos

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...
Linearization and Approximation01:26

Linearization and Approximation

Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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, the...
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
Modeling with Differential Equations01:25

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...

You might also read

Related Articles

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

Sort by
Same author

[Consistency between bioelectrical impedance analysis and dual-energy X-ray absorptiometry in body composition measurement in children aged 6-17 years in China].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2024
Same author

[Status and related factors on the drinking behavior among primary and secondary students in China rural middle and western regions in 2019].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2022
Same author

[Overweight and obesity status and its associated factors among primary and secondary school students in China rural middle and western regions].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2022
Same author

[Growth retardation of children and its influencing factors in the Nutrition Improvement Program for Rural Compulsory Education Students in 2019].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2022
Same author

[Anemia prevalence and its influencing factors among students involved in the Nutrition Improvement Program for Rural Compulsory Education Students in 2019].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2022
Same author

[Status and influencing factors on the leftover school meals among students the Nutrition Improvement Program for Rural Compulsory Education Students in 2019].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2022
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

A hybrid learning scheme combining EM and MASMOD algorithms for fuzzy local linearization modeling.

Q Gan1, C J Harris

  • 1Image, Speech and Intelligent Systems Research Group, Department of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK. qg@ecs.soton.ac.uk

IEEE Transactions on Neural Networks
|February 5, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a hybrid learning scheme for Fuzzy Local Linearization (FLL) modeling. The method enhances nonlinear system modeling for state estimation and control by combining adaptive splines and expectation-maximization algorithms.

Related Experiment Videos

Area of Science:

  • Control Engineering
  • Machine Learning
  • System Identification

Background:

  • Fuzzy Local Linearization (FLL) is a divide-and-conquer approach for complex nonlinear system modeling.
  • Accurate modeling is crucial for state estimation and control applications.

Purpose of the Study:

  • To propose a novel hybrid learning scheme for Fuzzy Local Linearization (FLL) modeling.
  • To improve the approximation ability, network parsimony, and error covariance estimation in FLL models.

Main Methods:

  • A hybrid learning scheme combining Modified Adaptive Spline Modeling (MASMOD) for antecedent parts (membership functions).
  • Expectation-Maximization (EM) algorithm for parameterizing consequent parts (local linear models).

Main Results:

  • The hybrid FLL model demonstrates approximation capabilities comparable to neuro-fuzzy networks.
  • Achieved a parsimonious network structure and provided valuable model error covariance information.

Conclusions:

  • The proposed hybrid learning scheme effectively models unknown nonlinear systems.
  • The method is suitable for applications requiring accurate state estimation and control with uncertainty quantification.