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

Complex Power01:14

Complex Power

380
Power engineers have introduced the concept of complex power to determine the cumulative effect of parallel loads. This idea plays a crucial role in power analysis because it encompasses all the details related to the power consumed by a specific load.
Complex power is defined as the multiplication of the voltage and the complex conjugate of the current. The magnitude of this power, known as apparent power, is measured in volt-amperes (VA). Notably, the angle of the complex power equates to the...
380
Properties of the z-Transform II01:16

Properties of the z-Transform II

110
The property of Accumulation in signal processing is derived by analyzing the accumulated sum of a discrete-time signal and using the time-shifting property to determine its z-transform. This principle reveals that the z-transform of the summed signal is related to the z-transform of the original signal by a multiplicative factor.
Moreover, the convolution property indicates that the convolution of two signals in the time domain corresponds to the product of their z-transforms in the frequency...
110
Properties of Fourier series II01:21

Properties of Fourier series II

139
Time scaling of signals is a crucial concept in signal processing that affects the Fourier series representation without altering its coefficients. The process modifies the fundamental frequency, thereby changing how the series represents the signal over time. This principle is essential in various applications, including audio and image processing, where signal manipulation is frequent. Understanding function symmetries is fundamental to simplifying the Fourier series.
A function f(t) is...
139
Properties of the z-Transform I01:17

Properties of the z-Transform I

173
The z-transform is a fundamental tool in digital signal processing, enabling the analysis of discrete-time systems through its various properties. It is an invaluable tool for analyzing discrete-time systems, offering a range of properties that simplify complex signal manipulations. One fundamental property is linearity. For any two discrete-time signals, the z-transform of their linear combination equals the same linear combination of their individual z-transforms. This property is essential...
173
Properties of Fourier series I01:20

Properties of Fourier series I

278
The Fourier series is a powerful tool in signal processing and communications, allowing periodic signals to be expressed as sums of sine and cosine functions. A foundational property of the Fourier series is linearity. If we consider two periodic signals, their linear combination results in a new signal whose Fourier coefficients are simply the corresponding linear combinations of the original signals' coefficients. This property is crucial in applications like frequency modulation (FM)...
278
Exponential Fourier series01:24

Exponential Fourier series

182
In audio signal processing, the exponential Fourier series plays a crucial role in sound synthesis, allowing complex sounds to be broken down into simpler sinusoidal components. This decomposition process is fundamental in analyzing and reconstructing musical notes and other audio signals. The exponential Fourier series expresses periodic signals as the sum of complex exponentials at both positive and negative harmonic frequencies, providing a powerful tool for signal analysis.
Euler's identity...
182

You might also read

Related Articles

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

Sort by
Same author

Interplay of NMDAR and AMPAR in the Pathophysiology of Alzheimer's, Parkinson, ALS, Huntington's, and Epilepsy: An Update in Therapeutic Perspective.

Current neuropharmacology·2026
Same author

Hyperseries in the non-Archimedean ring of Colombeau generalized numbers.

Monatshefte fur Mathematik·2022
Same author

Supremum, infimum and hyperlimits in the non-Archimedean ring of Colombeau generalized numbers.

Monatshefte fur Mathematik·2021
See all related articles

Related Experiment Video

Updated: Jun 11, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

784

Hyper-power series and generalized real analytic functions.

Diksha Tiwari1, Akbarali Mukhammadiev1, Paolo Giordano1

  • 1Faculty of Mathematics, University of Vienna, Wien, Austria.

Monatshefte Fur Mathematik
|September 30, 2024
PubMed
Summary

This study introduces generalized real analytic functions, extending Colombeau theory by analyzing hyper-power series and their convergence properties. These new functions offer greater flexibility than classical or Colombeau approaches.

Keywords:
Colombeau generalized numbersGeneralized functionsNon-Archimedean rings

More Related Videos

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
12:14

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

Published on: August 12, 2013

21.7K
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
06:40

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

10.1K

Related Experiment Videos

Last Updated: Jun 11, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

784
The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
12:14

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

Published on: August 12, 2013

21.7K
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
06:40

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

10.1K

Area of Science:

  • Non-Archimedean analysis
  • Generalized functions
  • Hyper-power series

Background:

  • Builds upon prior work on hyperseries in Colombeau generalized numbers.
  • Classical analytic functions have limitations in certain mathematical domains.

Purpose of the Study:

  • To define and investigate one-variable generalized real analytic functions.
  • To analyze hyper-power series, including their radius of convergence and algebraic properties.

Main Methods:

  • Analysis of radius of convergence for hyper-power series.
  • Proving classical results for hyper-power series (algebraic operations, composition, reciprocal).
  • Defining and studying generalized real analytic functions, including derivation, integration, and identity theorem.

Main Results:

  • Established classical results for hyper-power series.
  • Introduced generalized real analytic functions with enhanced flexibility.
  • Demonstrated that Colombeau real analytic functions are a subset of generalized real analytic functions.

Conclusions:

  • Generalized real analytic functions are less rigid than classical and Colombeau theories.
  • These functions can encompass non-analytic smooth functions and distributions like the Dirac delta.
  • The study expands the scope of analytic function theory within generalized number systems.