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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

376
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...
376
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

1.4K
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
1.4K
Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

1.0K
In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
1.0K
Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

468
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
468
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

805
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
805
Principle of Moments: Problem Solving01:30

Principle of Moments: Problem Solving

1.3K
The principle of moments is a fundamental concept in physics and engineering. It refers to the balancing of forces and moments around a point or axis, also known as the pivot. This principle is used in many real-life scenarios, including construction, sports, and daily activities like opening doors and pushing objects.
One such scenario involves a pole placed in a three-dimensional system with a cable attached. When a tension is applied to the cable, the moment about the z-axis passing through...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Intravenous transplantation of mesenchymal stem cells improves cardiac performance after acute myocardial ischemia in female rats.

Transplant international : official journal of the European Society for Organ Transplantation·2006
Same author

[Effects of mechanical tensile stress on the expression of ICAM-1 mRNA in osteoblasts differentiated from rBMSCs].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition·2006
Same author

[Effects of osteoporosis on experimental tooth movement in aged rats].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition·2006
Same author

MCALIGN2: faster, accurate global pairwise alignment of non-coding DNA sequences based on explicit models of indel evolution.

BMC bioinformatics·2006
Same author

[Managements of masked mastoiditis].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2006
Same author

Neuronal SIRT1 activation as a novel mechanism underlying the prevention of Alzheimer disease amyloid neuropathology by calorie restriction.

The Journal of biological chemistry·2006

Related Experiment Video

Updated: Mar 7, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.3K

A Two-Time-Scale Neurodynamic Approach to Constrained Minimax Optimization.

Xinyi Le, Jun Wang

    IEEE Transactions on Neural Networks and Learning Systems
    |February 18, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel two-time-scale neurodynamic method for constrained minimax optimization. Coupled recurrent neural networks effectively solve complex optimization problems, demonstrating robust performance in control applications.

    More Related Videos

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
    07:34

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

    Published on: March 25, 2014

    10.3K

    Related Experiment Videos

    Last Updated: Mar 7, 2026

    Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
    08:45

    Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

    Published on: October 24, 2012

    15.3K
    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
    07:34

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

    Published on: March 25, 2014

    10.3K

    Area of Science:

    • Control Systems Engineering
    • Computational Neuroscience
    • Optimization Theory

    Background:

    • Minimax optimization problems are prevalent in various scientific and engineering fields.
    • Traditional methods can be computationally intensive or struggle with complex constraints.
    • Recurrent neural networks offer a dynamic approach to solving optimization tasks.

    Purpose of the Study:

    • To develop a novel two-time-scale neurodynamic approach for constrained minimax optimization.
    • To utilize coupled recurrent neural networks for simultaneous minimization and maximization.
    • To demonstrate the efficacy of the proposed method in control applications.

    Main Methods:

    • A two-time-scale neurodynamic system comprising two coupled recurrent neural networks.
    • One network is dedicated to minimizing the objective function, the other to maximization.
    • The system operates with different time scales to achieve convergence.

    Main Results:

    • The coupled neurodynamic systems effectively solve constrained minimax optimization problems.
    • The approach demonstrates good performance and characteristics across various examples.
    • Successful application to H∞ model predictive control problems was achieved.

    Conclusions:

    • The proposed two-time-scale neurodynamic approach is a viable and effective method for constrained minimax optimization.
    • This neurodynamic strategy shows promise for advanced control system design, particularly in H∞ control.
    • The study highlights the potential of coupled neural networks in addressing complex optimization challenges.