On the Convergence of Random Fourier--Jacobi Series in $L_{[-1,1]}^{p,(\eta,\tau)}$ space
Partiswari Maharana, Sabita Sahoo

TL;DR
This paper studies the convergence of random Fourier--Jacobi series in weighted $L^p$ spaces, analyzing how the choice of coefficients and stochastic processes affect convergence and continuity of the series sum.
Contribution
It establishes convergence conditions for random Fourier--Jacobi series with coefficients from weighted $L^p$ spaces and examines the continuity of the resulting sum functions.
Findings
Convergence depends on the choice of Fourier--Jacobi coefficients and stochastic processes.
The series converges in the weighted $L^p$ space under certain conditions.
Continuity of the sum functions is established under specific settings.
Abstract
Liu and Liu introduced the random Fourier transform, which is a random Fourier series in Hermite functions, and applied it to image encryption and decryption. They expected its applications in optics and information technology. These motivated us to look into random Fourier series in orthogonal polynomials. Recently, we have established the convergence of random Fourier--Jacobi series where are the orthonormal Jacobi polynomials are random variables associated with stochastic processes like the Wiener process, the symmetric stable process, and the scalars are the Fourier--Jacobi coefficients of functions in some classes of continuous functions. It is observed that the mode of convergence of the random series depends on the choice of the scalars and the stochastic…
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Taxonomy
TopicsMathematical functions and polynomials · Approximation Theory and Sequence Spaces · Mathematical Analysis and Transform Methods
