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

Properties of DTFT I01:24

Properties of DTFT I

936
In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
936
Basic signals of Fourier Transform01:07

Basic signals of Fourier Transform

1.3K
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
1.3K
Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

896
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]...
896
Discrete Fourier Transform01:15

Discrete Fourier Transform

1.2K
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
1.2K
Discrete-time Fourier transform01:26

Discrete-time Fourier transform

1.4K
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...
1.4K
Properties of DTFT II01:24

Properties of DTFT II

701
In the study of discrete-time signal processing, understanding the properties of the Discrete-Time Fourier Transform (DTFT) is crucial for analyzing and manipulating signals in the frequency domain. Several properties, including frequency differentiation, convolution, accumulation, and Parseval's relation, offer powerful tools for signal analysis.
The frequency differentiation property is illustrated by considering a DTFT pair and differentiating both sides with respect to ω.
701

You might also read

Related Articles

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

Sort by
Same author

A Multi-Teacher Knowledge Distillation Framework for Enhancing the Robustness of Automated Sperm Morphology Assessment.

Diagnostics (Basel, Switzerland)·2026
Same author

Adaptive Logit Fusion for Mitigating Class Imbalance in Multi-Category Sperm Morphology Assessment.

Life (Basel, Switzerland)·2026
Same author

Gated Attention-Augmented Double U-Net for White Blood Cell Segmentation.

Journal of imaging·2025
Same author

Efficacy of synchronized diabetes monitoring system in patients with type 2 diabetes: Preliminary results of a pilot, randomized clinical trial.

Primary care diabetes·2025
Same author

End-to-end CNN-based detection of permanent first molars and prediction of root development stages from panoramic radiographs.

Scientific reports·2025
Same author

A mixture of attention experts-embedded flow-based generative model to create synthetic cells in single-cell RNA-Seq datasets.

PLoS computational biology·2025
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

Related Experiment Video

Updated: Apr 18, 2026

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180&#176; Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

12.0K

Symmetrical directional dual-tree complex wavelet packet transform.

Gorkem Serbes, Halil Ozcan Gulcur, Nizamettin Aydin

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 9, 2015
    PubMed
    Summary
    This summary is machine-generated.

    A novel symmetrical directional complex discrete wavelet packet transform simplifies quadrature signal processing. This method reduces computational complexity by eliminating traditional filter techniques for directional information mapping.

    More Related Videos

    Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
    08:42

    Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

    Published on: September 3, 2021

    3.7K
    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

    10.4K

    Related Experiment Videos

    Last Updated: Apr 18, 2026

    Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180&#176; Curved Artery Test Section
    11:00

    Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

    Published on: July 19, 2016

    12.0K
    Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
    08:42

    Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

    Published on: September 3, 2021

    3.7K
    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

    10.4K

    Area of Science:

    • Signal Processing
    • Wavelet Transforms
    • Biomedical Engineering

    Background:

    • Quadrature signals are commonly used in various signal processing applications.
    • Directional information extraction often requires complex filtering techniques.
    • Existing methods for directional signal conversion can be computationally intensive.

    Purpose of the Study:

    • To propose a new symmetrical directional complex discrete wavelet packet transform.
    • To enable direct application to quadrature format signals.
    • To reduce computational complexity in directional information mapping.

    Main Methods:

    • Development of a symmetrical directional complex discrete wavelet packet transform.
    • Direct decomposition of quadrature signals, mapping directional information.
    • Elimination of traditional symmetrical phasing filter techniques.

    Main Results:

    • The proposed transform can be directly applied to quadrature signals.
    • Directional information is mapped during the decomposition stage.
    • Significant reduction in computational complexity compared to traditional methods.
    • Successful performance evaluation using real quadrature embolic signals.

    Conclusions:

    • The symmetrical directional complex discrete wavelet packet transform offers an efficient alternative for processing quadrature signals.
    • This method simplifies the conversion of quadrature signals to directional signals.
    • The reduced computational complexity makes it suitable for real-time applications.