Related Experiment Video

Updated: Jun 12, 2026

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

LULU operators and discrete pulse transform for multi-dimensional arrays

Roumen Anguelov, Inger Fabris-Rotelli

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |May 21, 2010
    PubMed

    More Related Videos

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform06:25

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

    Published on: February 12, 2014

    Multiplexing Focused Ultrasound Stimulation with Fluorescence Microscopy08:39

    Multiplexing Focused Ultrasound Stimulation with Fluorescence Microscopy

    Published on: January 7, 2019

    Related Concept Videos

    Convolution: Math, Graphics, and Discrete Signals01:24

    Convolution: Math, Graphics, and Discrete Signals

    In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
    To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
    Convolution Properties I01:20

    Convolution Properties I

    Convolution computations can be simplified by utilizing their inherent properties.
    The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
    Definition of Laplace Transform01:22

    Definition of Laplace Transform

    The Laplace transform is an indispensable mathematical technique for simplifying the resolution of differential equations by converting them into more manageable algebraic expressions. The Laplace transform of a function is denoted by L[x(t)], where x(t) is the time-domain function. The laplace transform is mathematically expressed as
    Rectangular and Triangular Pulse Function01:19

    Rectangular and Triangular Pulse Function

    The unit rectangular pulse function is mathematically represented by a rectangular function centered at the origin with a height of one unit. This function is defined by two parameters: T, which specifies the center location of the pulse along the time axis, and τ, which determines the pulse duration.
    For example, consider a rectangular pulse with a 5V amplitude, a 3-second duration, and centered at t=2 seconds. This pulse can be expressed using the rectangular function, written as,
    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]...
    Discrete-time Fourier transform01:26

    Discrete-time Fourier transform

    The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
    One of the notable...