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

Vector Representation of Complex Numbers01:16

Vector Representation of Complex Numbers

547
Complex numbers, represented in Cartesian coordinates, can also be visualized as vectors. These vectors can be expressed in polar form, emphasizing their magnitude and angle. When a complex number is input into a function, the output is another complex number, highlighting the function's zero point from which the vector representation can originate.
Consider a function defined as the product of the complex factors in the numerator divided by the product of the complex factors in the...
547
State Space Representation01:27

State Space Representation

571
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...
571
Control Volume and System Representations01:16

Control Volume and System Representations

1.6K
Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface.  For instance, in the case of water...
1.6K
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

205
The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all...
205
Angular Momentum01:21

Angular Momentum

814
Angular momentum characterizes an object's rotational motion and is defined as the moment of its linear momentum about a specified point O. When a particle moves along a curved path in the x-y plane, the scalar formulation calculates the magnitude of its angular momentum, utilizing the moment arm (d), representing the perpendicular distance from point O to the line of action of the linear momentum. Despite being scalar in formulation, angular momentum is inherently a vector quantity. Its...
814
Partial Fractions01:28

Partial Fractions

219
A partial fraction is a component of a rational expression represented as the sum of simpler fractions. When a rational function is expressed as a ratio of two polynomials, it can often be decomposed into a sum of fractions whose denominators are simpler polynomials, typically linear or irreducible quadratic factors. This process is called partial fraction decomposition, and it is used to simplify complex expressions for integration, solving equations, or analysis.Partial fraction decomposition...
219

You might also read

Related Articles

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

Sort by
Same author

Physicochemical properties and structure of modified potato starch granules and their complex with tea polyphenols.

International journal of biological macromolecules·2020
Same author

Musashi1 expression is negatively correlated with numb expression in brain metastases.

Medicine·2020
Same author

Comparison of Surgical Techniques in Living Donor Nephrectomy: A Systematic Review and Bayesian Network Meta-Analysis.

Annals of transplantation·2020
Same author

Synthetic Routes for Heteroatom-Containing Alkylated/Arylated Polycyclic Aromatic Hydrocarbons.

Angewandte Chemie (International ed. in English)·2020
Same author

Insight Derived from Molecular Dynamics Simulation into the Selectivity Mechanism Targeting <i>c-MYC</i> G-Quadruplex.

The journal of physical chemistry. B·2020
Same author

Internal carotid artery rupture successfully rescued after resection of locally advanced mucosal malignant melanoma of the eustachian tube: a case report.

The Journal of international medical research·2020

Related Experiment Video

Updated: Jan 31, 2026

Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics
12:26

Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics

Published on: August 27, 2013

17.9K

Partial Angular Sparse Representation Based DOA Estimation Using Sparse Separate Nested Acoustic Vector Sensor Array.

Jianfeng Li1,2,3, Zheng Li4, Xiaofei Zhang5,6

  • 1College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China. lijianfeng@hhu.edu.cn.

Sensors (Basel, Switzerland)
|December 20, 2018
PubMed
Summary

This study introduces a novel method for direction of arrival (DOA) estimation using a sparse separate nested acoustic vector sensor (SSN-AVS) array. The approach enhances accuracy and reduces complexity compared to existing methods.

Keywords:
DOA estimationoff-grid sourcespartial angular sparse representationsparse separate nested acoustic vector sensor array

More Related Videos

Synthesis, Cellular Delivery and In vivo Application of Dendrimer-based pH Sensors
16:19

Synthesis, Cellular Delivery and In vivo Application of Dendrimer-based pH Sensors

Published on: September 10, 2013

12.3K
A Microfluidic Platform for Precision Small-volume Sample Processing and Its Use to Size Separate Biological Particles with an Acoustic Microdevice
11:32

A Microfluidic Platform for Precision Small-volume Sample Processing and Its Use to Size Separate Biological Particles with an Acoustic Microdevice

Published on: November 23, 2015

14.4K

Related Experiment Videos

Last Updated: Jan 31, 2026

Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics
12:26

Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics

Published on: August 27, 2013

17.9K
Synthesis, Cellular Delivery and In vivo Application of Dendrimer-based pH Sensors
16:19

Synthesis, Cellular Delivery and In vivo Application of Dendrimer-based pH Sensors

Published on: September 10, 2013

12.3K
A Microfluidic Platform for Precision Small-volume Sample Processing and Its Use to Size Separate Biological Particles with an Acoustic Microdevice
11:32

A Microfluidic Platform for Precision Small-volume Sample Processing and Its Use to Size Separate Biological Particles with an Acoustic Microdevice

Published on: November 23, 2015

14.4K

Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • Direction of Arrival (DOA) estimation is crucial in various applications.
  • Traditional acoustic vector sensor (AVS) arrays face limitations in degrees of freedom and resolution.
  • Sparse array geometries offer potential for improved performance.

Purpose of the Study:

  • To develop a partial angular sparse representation (SR)-based DOA estimation method.
  • To improve traditional AVS arrays by separating sensor components into nested sparse geometries.
  • To achieve high-resolution and unique DOA estimation with reduced computational complexity.

Main Methods:

  • Utilizing a sparse separate nested acoustic vector sensor (SSN-AVS) array.
  • Employing partial angular sparse representation (SR) by exploiting cyclic phase ambiguity.
  • Implementing joint sparse recovery to amend grid offset and unitary transformation for real-valued data.
  • Combining ambiguous and unambiguous angle estimations for unique DOA results.

Main Results:

  • The proposed SSN-AVS array geometry achieves a large degrees of freedom (DOF).
  • Partial SR effectively exploits cyclic phase ambiguity for angle estimation.
  • Joint sparse recovery and unitary transformation enhance estimation accuracy.
  • The developed algorithm provides high-resolution, unique DOA estimation.

Conclusions:

  • The proposed partial angular SR-based method with SSN-AVS offers superior DOA estimation performance.
  • The algorithm demonstrates lower complexity compared to state-of-the-art AVS-based DOA methods.
  • Simulation results confirm the effectiveness and advantages of the developed approach.