Related Experiment Video

Updated: Oct 12, 2025

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

10.0K

Complex field reconstruction of optical OFDM signals based on temporal transport-of-intensity equation

Masayuki Matsumoto

    Optics Express
    |November 23, 2021
    PubMed

    More Related Videos

    Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture09:04

    Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

    Published on: February 23, 2018

    9.6K
    Quasi-light Storage for Optical Data Packets07:45

    Quasi-light Storage for Optical Data Packets

    Published on: February 6, 2014

    11.0K

    Related Concept Videos

    Reconstruction of Signal using Interpolation01:10

    Reconstruction of Signal using Interpolation

    Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
    398
    Properties of Fourier Transform I01:21

    Properties of Fourier Transform I

    The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
    In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
    316
    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.
    For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
    139
    Linear Approximation in Frequency Domain01:26

    Linear Approximation in Frequency Domain

    Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
    In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
    165
    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...
    456
    Discrete-Time Fourier Series01:20

    Discrete-Time Fourier Series

    The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
    For a discrete-time periodic signal x[n]...
    401