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Related Concept Videos

Classification of Systems-II01:31

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
Traveling Waves: Lossless Lines01:27

Traveling Waves: Lossless Lines

The provided content explores the behavior of traveling waves on single-phase lossless transmission lines. It begins with a single-phase two-wire lossless transmission line of length Δx, characterized by a loop inductance LH/m and a line-to-line capacitance C F/m. These parameters result in a series inductance LΔx and a shunt capacitance CΔx.
Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...
Basic Continuous Time Signals01:22

Basic Continuous Time Signals

Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
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Basic Discrete Time Signals01:16

Basic Discrete Time Signals

The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
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Related Experiment Video

Updated: May 23, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

Delayed uncoupled continuous-time random walks do not provide a model for the telegraph equation.

S A Rukolaine1, A M Samsonov

  • 1The Ioffe Physical Technical Institute of the Russian Academy of Sciences, 26 Polytekhnicheskaya, St. Petersburg 194021, Russia. rukol@ammp.ioffe.ru

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|April 3, 2012
PubMed
Summary

Delayed continuous-time random walks (DCTRWs) do not model the one-dimensional telegraph equation. The diffusion equation better approximates DCTRWs than the telegraph equation, challenging previous assumptions.

Related Experiment Videos

Last Updated: May 23, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

Area of Science:

  • Physics
  • Mathematical Modeling
  • Stochastic Processes

Background:

  • Delayed continuous-time random walks (DCTRWs) have been proposed as a microscopic model for the one-dimensional telegraph equation.
  • This proposition is questionable due to the infinite particle velocity in DCTRWs versus the finite propagation speed in the telegraph equation.

Purpose of the Study:

  • To investigate the accuracy of the telegraph equation as an approximation for DCTRWs.
  • To compare the approximation quality of the diffusion equation and the telegraph equation for DCTRWs.

Main Methods:

  • Analysis of the mathematical relationship between DCTRWs, the telegraph equation, and the diffusion equation.
  • Evaluation of approximation accuracy using the L(2) norm.

Main Results:

  • The diffusion equation provides a better L(2) norm approximation to DCTRWs compared to the telegraph equation.
  • The study demonstrates that the telegraph equation is not an accurate microscopic model for DCTRWs.

Conclusions:

  • Delayed continuous-time random walks (DCTRWs) do not offer a correct microscopic interpretation of the one-dimensional telegraph equation.
  • The kinetic model of the telegraph equation is distinct from models based on DCTRWs.