Related Experiment Video

Updated: Nov 2, 2025

Measurement of Spatial Stability in Precision Grip
09:36

Measurement of Spatial Stability in Precision Grip

Published on: June 4, 2020

3.4K

Global Stabilization for a Class of Stochastic Nonlinear Time-Delay Systems With Unknown Measurement Drifts and Its

Qingtan Meng, Qian Ma

    IEEE Transactions on Neural Networks and Learning Systems
    |June 7, 2021
    PubMed

    More Related Videos

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials12:03

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

    Published on: May 25, 2019

    8.6K
    Sample Drift Correction Following 4D Confocal Time-lapse Imaging10:04

    Sample Drift Correction Following 4D Confocal Time-lapse Imaging

    Published on: April 12, 2014

    16.7K

    Related Concept Videos

    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,...
    176
    Linear time-invariant Systems01:23

    Linear time-invariant Systems

    A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
    The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
    574
    BIBO stability of continuous and discrete -time systems01:24

    BIBO stability of continuous and discrete -time systems

    System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
    To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
    634
    Stability01:28

    Stability

    The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
    The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
    220
    Propagation of Uncertainty from Systematic Error01:10

    Propagation of Uncertainty from Systematic Error

    The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
    1.1K
    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.
    237