Related Experiment Video

Updated: Nov 12, 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

1.9K

Distributed Robust Kalman Filtering for Markov Jump Systems With Measurement Loss of Unknown Probabilities

Hui Li, Liping Yan, Yuanqing Xia

    IEEE Transactions on Cybernetics
    |March 19, 2021
    PubMed

    More Related Videos

    Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules10:20

    Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

    Published on: September 5, 2019

    8.5K
    Establishing a Competing Risk Regression Nomogram Model for Survival Data04:57

    Establishing a Competing Risk Regression Nomogram Model for Survival Data

    Published on: October 23, 2020

    10.5K

    Related Concept Videos

    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
    Propagation of Uncertainty from Random Error00:59

    Propagation of Uncertainty from Random Error

    An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
    1.4K
    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....
    714
    State Space Representation01:27

    State Space Representation

    The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
    Consider an RLC circuit, a...
    359
    Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

    Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

    Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
    The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
    163
    Probability in Statistics01:14

    Probability in Statistics

    Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
    An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
    20.0K