Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Blind Procedures

Blind Procedures

Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...

Blinding

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein Networks

Protein Networks

No description available

Network Covalent Solids

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...

Sinusoidal Sources

Sinusoidal Sources

Direct current (DC) refers to an electric current that flows in a single direction, maintaining a constant polarity. This is in contrast to alternating current (AC), which periodically changes its direction and magnitude. AC forms the backbone of modern electricity transmission and distribution systems due to its efficient long-distance transmission capabilities.
In homes, the power supplies use sinusoidal sources to provide electricity. These sources generate a voltage that varies sinusoidally...

You might also read

Related Articles

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

Sort by

Same author

Synthesis and micellization of amphiphilic brush-coil block copolymer based on poly(epsilon-caprolactone) and PEGylated polyphosphoester.

Biomacromolecules·2006

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

Search research articles

Related Experiment Video

Updated: Feb 1, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

A network model for blind source extraction in various ill-conditioned cases.

Yuanqing Li¹, Jun Wang

¹Institute of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China. auyqli@scut.edu.cn

Neural Networks : the Official Journal of the International Neural Network Society

|September 13, 2005

Summary

This summary is machine-generated.

This study introduces a simple network model for blind source extraction, defining conditions for successful signal recovery even in challenging, ill-conditioned scenarios. The research develops a cost function and learning algorithm, validated by simulations for robust performance.

More Related Videos

Blind Endotracheal Intubation in Neonatal Rabbits

Blind Endotracheal Intubation in Neonatal Rabbits

Published on: February 26, 2021

Perfusable Vascular Network with a Tissue Model in a Microfluidic Device

Perfusable Vascular Network with a Tissue Model in a Microfluidic Device

Published on: April 4, 2018

Related Experiment Videos

Last Updated: Feb 1, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Blind Endotracheal Intubation in Neonatal Rabbits

Blind Endotracheal Intubation in Neonatal Rabbits

Published on: February 26, 2021

Perfusable Vascular Network with a Tissue Model in a Microfluidic Device

Perfusable Vascular Network with a Tissue Model in a Microfluidic Device

Published on: April 4, 2018

Area of Science:

Signal Processing
Machine Learning
Information Theory

Background:

Blind source extraction (BSE) is crucial for separating mixed signals.
Ill-conditioned scenarios, such as singular mixing matrices or unequal sensor/source numbers, pose significant challenges to BSE.
Existing methods often struggle with these complex and underdetermined or rank-deficient situations.

Purpose of the Study:

To analyze the extractability of sources in various ill-conditioned scenarios using a simple extraction network model.
To establish necessary and sufficient conditions for successful blind source extraction.
To develop a cost function and an unsupervised learning algorithm for the proposed extraction network.

Main Methods:

Analysis of extractability for specific ill-conditioned cases: singular square mixing matrix, fewer sensors than sources, rank-deficient mixing matrix (more sensors than sources), and unknown source number with rank deficiency.
Development of a novel cost function tailored for the extraction network.
Implementation of an unsupervised learning algorithm to train the extraction network.

Main Results:

Derivation of a necessary and sufficient condition for source extractability in the analyzed ill-conditioned cases.
Successful development of a cost function and an unsupervised learning algorithm for the extraction network model.
Simulation results demonstrating the validity of theoretical findings and the effectiveness of the learning algorithm.

Conclusions:

The proposed simple extraction network model effectively addresses blind source extraction in various ill-conditioned scenarios.
The established conditions and developed learning algorithm provide a robust framework for signal separation.
The findings contribute to advancing blind source extraction techniques, particularly in complex and challenging environments.