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

Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

882
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
882
Multimachine Stability01:25

Multimachine Stability

620
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
620
Network Function of a Circuit01:25

Network Function of a Circuit

983
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
983
Block Diagram Reduction01:22

Block Diagram Reduction

618
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
618
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.0K
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...
1.0K
Relation between Mathematical Equations and Block Diagrams01:20

Relation between Mathematical Equations and Block Diagrams

3.7K
In a spring-mass-damper system, the second-order differential equation describes the dynamic behavior of the system. When transformed into the Laplace domain under zero initial conditions, this equation can be effectively analyzed and manipulated. The transformation into the Laplace domain converts differential equations into algebraic equations, simplifying the process of isolating the output.
3.7K

You might also read

Related Articles

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

Sort by
Same author

Multi-bit Boolean model for chemotactic drift of <i>Escherichia coli</i>.

IET systems biology·2021
Same author

Supercritical and subcritical Hopf-bifurcations in a two-delayed prey-predator system with density-dependent mortality of predator and strong Allee effect in prey.

Bio Systems·2019
Same author

Fault detection and therapeutic intervention in gene regulatory networks using SAT solvers.

Bio Systems·2019
Same author

Learning a Probabilistic Boolean Network model from biological pathways and time-series expression data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2017
Same author

A Boolean approach to bacterial chemotaxis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2017
Same author

Inference of asynchronous Boolean network from biological pathways.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2016

Related Experiment Video

Updated: Mar 17, 2026

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks
07:50

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks

Published on: November 25, 2015

15.0K

Estimation of delays in generalized asynchronous Boolean networks.

Haimabati Das1, Ritwik Kumar Layek

  • 1Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, 721302, India. haimabati@ece.iitkgp.ernet.in ritwik@ece.iitkgp.ernet.in.

Molecular Biosystems
|July 29, 2016
PubMed
Summary
This summary is machine-generated.

A new generalized asynchronous Boolean network (GABN) model accurately simulates cellular dynamics. This computational biology approach incorporates protein activation/deactivation delays for enhanced biological realism in network modeling.

Related Experiment Videos

Last Updated: Mar 17, 2026

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks
07:50

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks

Published on: November 25, 2015

15.0K

Area of Science:

  • Computational Biology
  • Systems Biology
  • Biophysics

Background:

  • Boolean networks are widely used for modeling gene regulatory networks.
  • Existing models often simplify biological processes, lacking computational efficiency or biological realism.

Purpose of the Study:

  • To introduce a novel Generalized Asynchronous Boolean Network (GABN) model.
  • To enhance the biological accuracy of Boolean networks by incorporating differential protein activation and deactivation delays.

Main Methods:

  • Developed a continuous-time, discrete-state GABN model.
  • Utilized prior knowledge of regulatory network logic and experimental transcriptional parameters for GABN synthesis.
  • Simulated network motifs and the p53-signaling pathway.

Main Results:

  • The GABN model effectively captures biological dynamics while maintaining computational efficiency.
  • Demonstrated the model's applicability to well-studied network motifs and larger biological networks.
  • Successfully simulated the p53-signaling pathway response to γ-irradiation, providing indirect validation.

Conclusions:

  • The GABN model offers a powerful and biologically realistic framework for systems biology research.
  • The incorporation of differential delays significantly improves the accuracy of regulatory network modeling.
  • The GABN approach shows promise for analyzing complex signaling pathways and large-scale biological networks.