Related Experiment Video

Updated: Sep 30, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.5K

Positive Consensus of Fractional-Order Multiagent Systems Over Directed Graphs

Jason J R Liu, James Lam, Ka-Wai Kwok

    IEEE Transactions on Neural Networks and Learning Systems
    |March 16, 2022
    PubMed

    More Related Videos

    A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents08:38

    A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

    Published on: November 21, 2019

    7.8K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.3K

    Related Concept Videos

    Alternative Sets of Equilibrium Equations01:31

    Alternative Sets of Equilibrium Equations

    When analyzing the behavior of structures, engineers often rely on the concept of equilibrium. This refers to the state where all forces and moments acting on a system balance each other, resulting in no net movement or rotation. In many cases, equilibrium can be described by a set of standard equations. However, in some situations, alternative sets of equilibrium equations must be used to describe the system's behavior accurately.
    One example of such a situation can be observed in a...
    486
    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...
    185
    First Order Systems01:21

    First Order Systems

    First-order systems, such as RC circuits, are foundational in understanding dynamic systems due to their straightforward input-output relationship. Analyzing their responses to different input functions under zero initial conditions reveals significant insights into system behavior.
    When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
    174
    Second Order systems I01:20

    Second Order systems I

    A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
    By reinterpreting the system, one can derive the closed-loop transfer function, which...
    270
    Second Order systems II01:18

    Second Order systems II

    In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
    193
    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...
    109