Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Upsampling

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

Sampling Continuous Time Signal

Sampling Continuous Time Signal

In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...

Sampling Theorem

Sampling Theorem

In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.

Sampling Methods: Overview

Sampling Methods: Overview

A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling.
In analytical chemistry, the choice of...

Aliasing

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...

Sampling Methods: Sample Types

Sampling Methods: Sample Types

Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...

You might also read

Related Articles

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

Sort by

Same author

[Observance of antifibrotic treatment in the French OPALE support program for patients with pulmonary fibrosis].

Revue des maladies respiratoires·2026

Same author

Hierarchical dynamics and time-length scale superposition in glassy suspensions of ultra-low crosslinked microgels.

The Journal of chemical physics·2026

Same author

Congenital tarsal kink syndrome.

Journal francais d'ophtalmologie·2026

Same author

Decoupling Structure and Elasticity in Colloidal Gels Under Isotropic Compression.

Physical review letters·2026

Same author

Probing microscopic dynamics in a uni-axially strained polymer network with light scattering.

Soft matter·2025

Same author

Initial stages of rejuvenation of vapor-deposited glasses during isothermal annealing: Contrast between experiment and simulation.

The Journal of chemical physics·2024

Same journal

Interplay of Anisotropy, Dzyaloshinskii Moriya Interaction and Symmetry breaking Fields in a 2D XY Ferromagnet.

Journal of physics. Condensed matter : an Institute of Physics journal·2026

Same journal

Single-molecule electron transport near a charge-trapping orbital-level alignment.

Journal of physics. Condensed matter : an Institute of Physics journal·2026

Same journal

Δ<sub>T</sub>Noise as a Robust Diagnostic for Chiral, Helical and Trivial Edge Modes.

Journal of physics. Condensed matter : an Institute of Physics journal·2026

Same journal

A Quantum Framework for Negative Magnetoresistance in Multi-Weyl Semimetals.

Journal of physics. Condensed matter : an Institute of Physics journal·2026

Same journal

Magnetic anisotropy and electronic structure in surface-supported single rare-earth atom magnets: a topical review.

Journal of physics. Condensed matter : an Institute of Physics journal·2026

Same journal

Modeling thermal transport in AlN/GaN superlattices and heterostructures with machine-learned force fields.

Journal of physics. Condensed matter : an Institute of Physics journal·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 26, 2026

Advanced Experimental Methods for Low-temperature Magnetotransport Measurement of Novel Materials

Advanced Experimental Methods for Low-temperature Magnetotransport Measurement of Novel Materials

Published on: January 21, 2016

An efficient scheme for sampling fast dynamics at a low average data acquisition rate.

A Philippe¹, S Aime, V Roger

¹Laboratoire Charles Coulomb (L2C), UMR 5221 CNRS-Université de Montpellier, Montpellier, France.

Journal of Physics. Condensed Matter : an Institute of Physics Journal

|January 26, 2016

Summary

This summary is machine-generated.

We developed a new data sampling method using variable delays to reduce data rates while capturing fast dynamics. This technique is effective for studying colloidal suspensions with cameras.

More Related Videos

Blood Flow Imaging with Ultrafast Doppler

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy

Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy

Published on: December 1, 2021

Related Experiment Videos

Last Updated: Mar 26, 2026

Advanced Experimental Methods for Low-temperature Magnetotransport Measurement of Novel Materials

Advanced Experimental Methods for Low-temperature Magnetotransport Measurement of Novel Materials

Published on: January 21, 2016

Blood Flow Imaging with Ultrafast Doppler

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy

Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy

Published on: December 1, 2021

Area of Science:

Physics
Materials Science
Physical Chemistry

Background:

Studying the dynamics of colloidal suspensions is crucial for understanding material properties.
High data acquisition rates can be a bottleneck in experiments observing fast dynamic processes.

Purpose of the Study:

To introduce a novel temporal data sampling scheme.
To reduce average data flow rates without losing information on fast time scales.
To demonstrate the practical implementation and effectiveness of the scheme.

Main Methods:

A temporal sampling scheme with variable delays between data acquisitions.
Implementation in light scattering and microscopy experiments.
Utilizing CMOS or CCD cameras for data detection.

Main Results:

The proposed scheme effectively reduces the average data flow rate.
Information on fast time-scale data evolution is successfully retained.
The method was validated in experiments on colloidal suspension dynamics.

Conclusions:

The variable delay sampling scheme offers an efficient approach for dynamic studies.
This method is practical for experiments involving colloidal systems and standard imaging detectors.
It enables reduced data handling while preserving critical dynamic information.