Related Experiment Video
Updated: Jan 22, 2026

08:38
Electrospray Deposition of Uniform Thickness Ge23Sb7S70 and As40S60 Chalcogenide Glass Films
Published on: August 19, 2016
9.1K
Uniform convergence of basic Fourier-Bessel series on a q-linear grid
L D Abreu1, R Álvarez-Nodarse2, J L Cardoso3
11Acoustics Research Institute, Austrian Academy of Sciences, Vienna, Austria.
Summary
This study explores Fourier-Bessel series on q-linear grids, establishing conditions for uniform convergence using q-orthogonal systems and the third Jackson q-Bessel function.
Area of Science:
- Mathematical Analysis
- Special Functions
- Fourier Analysis
Background:
- Fourier-Bessel series are essential tools in mathematical analysis.
- Understanding convergence properties is crucial for their application.
- Previous work has explored various orthogonal systems for series expansions.
Purpose of the Study:
- To investigate Fourier-Bessel series on a q-linear grid.
- To establish sufficient conditions for the uniform convergence of these series.
- To demonstrate the practical application of the convergence results.
Main Methods:
- Construction of complete q-orthogonal systems.
- Utilizing the third Jackson q-Bessel function.
- Derivation of sufficient conditions for uniform convergence.
Main Results:
- Sufficient conditions for uniform convergence of Fourier-Bessel series on a q-linear grid were obtained.
- The study provides a theoretical framework for analyzing these series.
- Convergence results were illustrated with specific examples.
Conclusions:
- The developed conditions provide valuable insights into the behavior of Fourier-Bessel series on q-linear grids.
- The findings contribute to the theory of special functions and Fourier analysis.
- The research validates the utility of q-orthogonal systems in convergence studies.
Related Concept Videos
Convergence of Fourier Series
386
The Fourier series is a powerful mathematical tool for representing periodic signals as an infinite sum of complex exponentials. In practice, this infinite series is truncated to a finite number of terms, yielding a partial sum. This truncation makes the approximation of the signal feasible but introduces certain challenges, particularly near discontinuities, known as the Gibbs phenomenon.
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
386
Trigonometric Fourier series
767
Fourier series is a foundational mathematical technique that decomposes periodic functions into an infinite series of sinusoidal harmonics. This method enables the representation of complex periodic signals as sums of simple sine and cosine functions, facilitating their analysis and interpretation in various fields, including signal processing, acoustics, and electrical engineering.
The trigonometric Fourier series specifically expresses a periodic function with a defined period T using sine...
The trigonometric Fourier series specifically expresses a periodic function with a defined period T using sine...
767
Exponential Fourier series
686
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...
Euler's identity...
686
Properties of Fourier series I
719
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) radio,...
719
Properties of Fourier series II
549
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...
A function f(t) is...
549
Discrete-Time Fourier Series
665
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]...
For a discrete-time periodic signal x[n]...
665

