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

Upsampling01:22

Upsampling

283
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...
283
Aliasing01:18

Aliasing

192
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...
192
Sampling Theorem01:15

Sampling Theorem

681
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.
681
Bandpass Sampling01:17

Bandpass Sampling

240
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
240
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

292
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...
292
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

107
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
107

You might also read

Related Articles

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

Sort by
Same author

CD73 blockade alleviates collagen-induced arthritis by inhibiting synovial fibroblast activity.

Iranian journal of basic medical sciences·2026
Same author

Design, Synthesis, and Biological Evaluation of a MyD88-Targeted Molecular Glue d21 for the Treatment of Acute Lung Injury.

Journal of medicinal chemistry·2026
Same author

APOL1-risk alleles modulate T-cell receptor signaling to promote allograft rejection.

The Journal of clinical investigation·2026
Same author

Multi-source Fusion Positioning Revisited by Drawing on Human Thinking Process.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Circulating cell-free mtDNA fragmentomics for early detection of gastric cancer and precancerous lesions.

Cell reports. Medicine·2026
Same author

Dual-balloon overlapping post-dilation for stent optimization in markedly dilated coronary artery.

Frontiers in cardiovascular medicine·2026

Related Experiment Video

Updated: Aug 16, 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

Equalization of camera-based channel to mitigate uncertain sampling for optical camera communications.

Ke Dong, Xizheng Ke, Mingjun Wang

    Optics Express
    |December 23, 2022
    PubMed
    Summary
    This summary is machine-generated.

    Uncertain sampling in optical camera communication degrades performance. This study proposes a channel equalization method to mitigate this issue by exploiting space-time relationships, improving data transmission reliability.

    More Related Videos

    Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion
    10:30

    Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

    Published on: September 4, 2013

    9.7K
    X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
    08:30

    X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

    Published on: September 11, 2011

    14.5K

    Related Experiment Videos

    Last Updated: Aug 16, 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
    Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion
    10:30

    Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

    Published on: September 4, 2013

    9.7K
    X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
    08:30

    X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

    Published on: September 11, 2011

    14.5K

    Area of Science:

    • Optical Camera Communication
    • Signal Processing
    • Wireless Communication

    Background:

    • Asynchronous optical camera communication (OCC) presents uncertain sampling, a core challenge degrading data transmission.
    • The camera channel's exposure effect is a primary source of this sampling uncertainty.

    Purpose of the Study:

    • To propose a novel channel equalization method to mitigate uncertain sampling in OCC.
    • To analyze the equalization error rate under varying under-sampling and over-exposure conditions.

    Main Methods:

    • Developed a parametric model for the camera-based channel's exposure effect.
    • Proposed a channel equalization technique exploiting the space-time relationship of spatial delayed pulse width modulation (PWM) waveforms from multiple light sources.
    • Analyzed equalization error rates based on duty cycles and exposure times.

    Main Results:

    • The proposed channel equalization method effectively mitigates uncertain sampling in OCC.
    • Numerical simulations and experimental results validate the method's availability and reliability.
    • Error rate analysis provides insights into performance under different operational parameters.

    Conclusions:

    • The developed channel equalization technique offers a viable solution to the inherent uncertain sampling problem in asynchronous OCC.
    • Exploiting space-time correlations is key to enhancing OCC data transmission performance.
    • The findings contribute to more robust and reliable optical wireless communication systems.