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

Cluster Sampling Method01:20

Cluster Sampling Method

11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

71
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...
71
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.1K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

515
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
515
Sampling Plans01:23

Sampling Plans

187
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
187
Stratified Sampling Method01:16

Stratified Sampling Method

12.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
12.0K

You might also read

Related Articles

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

Sort by
Same author

Distributed Estimation Techniques for Cyber-Physical Systems: A Systematic Review.

Sensors (Basel, Switzerland)·2019
Same author

Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks.

Sensors (Basel, Switzerland)·2018
See all related articles

Related Experiment Video

Updated: Jul 8, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.3K

A sequential approach for distributed set-membership estimation to exploit redundant information.

Luis Orihuela1

  • 1Dept. Ingeniería Electrónica, Sistemas Informáticos y Automática, Universidad de Huelva, Avda. de las Fuerzas Armadas s/n, Huelva, 21007, Huelva, Spain.

ISA Transactions
|December 14, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new distributed set-membership estimation method for linear systems. By leveraging redundant information from neighbors, it effectively reduces estimation uncertainty with minimal computational overhead.

Keywords:
Distributed estimationLinear time-invariant plantSequential observersSet-membership observerZonotopes

More Related Videos

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.1K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

Related Experiment Videos

Last Updated: Jul 8, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.3K
Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.1K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

Area of Science:

  • Control Systems Engineering
  • Estimation Theory
  • Distributed Systems

Background:

  • Decentralized estimation is crucial for large-scale systems where centralized processing is infeasible.
  • Existing methods often discard redundant information, leading to suboptimal performance.
  • Set-membership estimation provides guaranteed bounds on system states, essential for safety-critical applications.

Purpose of the Study:

  • To develop a novel distributed set-membership estimation algorithm for linear time-invariant (LTI) plants.
  • To effectively utilize redundant information shared among neighboring agents to improve estimation accuracy.
  • To analyze the computational cost and robustness of the proposed method.

Main Methods:

  • A sequential information exploitation strategy is employed, where agents use neighborhood data.
  • An innovation-routing table, integrating routing and subspace observability, is constructed.
  • Sequential filtering is applied to state vector modes decomposed into zonotopes.
  • The approach builds upon established centralized zonotopic observer techniques.

Main Results:

  • Simulation results demonstrate that utilizing redundant information significantly reduces estimation uncertainty.
  • The proposed method shows only a minor increase in computational cost compared to non-redundant approaches.
  • Numerical simulations analyze the method's sensitivity to various parameters.

Conclusions:

  • The novel distributed estimation approach effectively reduces uncertainty by exploiting redundant information.
  • The method offers a computationally efficient and robust solution for set-membership estimation in LTI systems.
  • This work advances distributed estimation techniques by integrating information sharing and set-based bounding.