On the Hilbert transform for Banach space valued functions

1982 ◽  
pp. 73-80 ◽  
Author(s):  
J. A. Gutierrez ◽  
H. E. Lacey
Keyword(s):  
Banach Space ◽  
Hilbert Transform ◽  
The Hilbert Transform

scholarly journals A note on UMD spaces and transference in vector-valued function spaces

1996 ◽  
Vol 39 (3) ◽  
pp. 485-490 ◽  
Author(s):  
N. H. Asmar ◽  
B. P. Kelly ◽  
S. Montgomery-Smith
Keyword(s):  
Banach Space ◽  
Hilbert Transform ◽  
Function Spaces ◽  
Conjugate Functions ◽  
Riesz Theorem ◽  
Umd Spaces ◽  
The Hilbert Transform ◽  
Vector Valued Function ◽  
Vector Valued

A Banach space X is called an HT space if the Hilbert transform is bounded from Lp(X) into Lp(X), where 1 < p < ∞. We introduce the notion of an ACF Banach space, that is, a Banach space X for which we have an abstract M. Riesz Theorem for conjugate functions in Lp(X), 1 < p < ∞. Berkson, Gillespie and Muhly [5] showed that X ∈ HT ⇒ X ∈ ACF. In this note, we will show that X ∈ ACF ⇒ X ∈ UMD, thus providing a new proof of Bourgain's result X ∈ HT ⇒ X ∈ UMD.

A space of slowly decreasing functions with pleasant Fourier transforms

1991 ◽  
Vol 119 (1-2) ◽  
pp. 73-86
Author(s):  
L. E. Fraenkel
Keyword(s):  
Banach Space ◽  
Fourier Transform ◽  
Bounded Variation ◽  
Hilbert Transform ◽  
Fourier Transforms ◽  
Weighting Function ◽  
The Fourier Transform ◽  
The Hilbert Transform ◽  
Decreasing Functions

SynopsisThe space in question is Aµ(R):=L1(R) + Bµ(R), where Bµ(R) is a Banach space that contains the “tails” (the dominant parts for large values of |x|) of certain slowly decreasing functions from R to R. Functions in Bµ(R) are of bounded variation, and the norm involves their variation and a weighting function. Theorems are proved only for Bµ(R), because those for L1(R) are known. The results concern the convolution of a function in Bµ(R) with one in L1(R), the Fourier transform acting on Bµ(R), and the signum rule for the Hilbert transform of functions in Bµ(R).

scholarly journals The Hilbert Transform and Orthogonal Martingales in Banach Spaces

2019 ◽  
Author(s):  
Adam Osękowski ◽  
Ivan Yaroslavtsev
Keyword(s):  
Banach Space ◽  
Singular Integral ◽  
Hilbert Transform ◽  
Real Line ◽  
Harmonic Functions ◽  
Integral Operators ◽  
Continuous Functions ◽  
Hilbert Transforms ◽  
Discrete Hilbert Transform ◽  
The Hilbert Transform

Abstract Let $X$ be a given Banach space, and let $M$ and $N$ be two orthogonal $X$-valued local martingales such that $N$ is weakly differentially subordinate to $M$. The paper contains the proof of the estimate $\mathbb E \Psi (N_t) \leq C_{\Phi ,\Psi ,X} \mathbb E \Phi (M_t)$, $t\geq 0$, where $\Phi , \Psi :X \to \mathbb R_+$ are convex continuous functions and the least admissible constant $C_{\Phi ,\Psi ,X}$ coincides with the $\Phi ,\Psi $-norm of the periodic Hilbert transform. As a corollary, it is shown that the $\Phi ,\Psi $-norms of the periodic Hilbert transform, the Hilbert transform on the real line, and the discrete Hilbert transform are the same if $\Phi $ is symmetric. We also prove that under certain natural assumptions on $\Phi $ and $\Psi $, the condition $C_{\Phi ,\Psi ,X}<\infty $ yields the UMD property of the space $X$. As an application, we provide comparison of $L^p$-norms of the periodic Hilbert transform to Wiener and Paley–Walsh decoupling constants. We also study the norms of the periodic, nonperiodic, and discrete Hilbert transforms and present the corresponding estimates in the context of differentially subordinate harmonic functions and more general singular integral operators.

Model of multicomponent narrow-band periodical non-stationary random signal

2020 ◽  
Vol 2020 (48) ◽  
pp. 17-24
Author(s):  
I.M. Javorskyj ◽  
◽  
R.M. Yuzefovych ◽  
P.R. Kurapov ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Real Time ◽  
Hilbert Transform ◽  
Spectral Properties ◽  
Narrow Band ◽  
Analytic Signal ◽  
Random Signal ◽  
Hilbert Transformation ◽  
The Hilbert Transform

The correlation and spectral properties of a multicomponent narrowband periodical non-stationary random signal (PNRS) and its Hilbert transformation are considered. It is shown that multicomponent narrowband PNRS differ from the monocomponent signal. This difference is caused by correlation of the quadratures for the different carrier harmonics. Such features of the analytic signal must be taken into account when we use the Hilbert transform for the analysis of real time series.

A Bayesian View on the Hilbert Transform and the Kramers-Kronig Transform of Electrochemical Impedance Data: Probabilistic Estimates and Quality Scores

2020 ◽  
Author(s):  
Jiapeng Liu ◽  
Ting Hei Wan ◽  
Francesco Ciucci
Keyword(s):  
Power Generation ◽  
Electrochemical Impedance Spectroscopy ◽  
Hilbert Transform ◽  
Electrochemical Impedance ◽  
The Self ◽  
Impedance Data ◽  
The Hilbert Transform ◽  
Validation Tests ◽  
Self Consistency ◽  
Mathematical Relations

<p>Electrochemical impedance spectroscopy (EIS) is one of the most widely used experimental tools in electrochemistry and has applications ranging from energy storage and power generation to medicine. Considering the broad applicability of the EIS technique, it is critical to validate the EIS data against the Hilbert transform (HT) or, equivalently, the Kramers–Kronig relations. These mathematical relations allow one to assess the self-consistency of obtained spectra. However, the use of validation tests is still uncommon. In the present article, we aim at bridging this gap by reformulating the HT under a Bayesian framework. In particular, we developed the Bayesian Hilbert transform (BHT) method that interprets the HT probabilistic. Leveraging the BHT, we proposed several scores that provide quick metrics for the evaluation of the EIS data quality.<br></p>

scholarly journals A Radial Basis Function Finite Difference Scheme for the Benjamin–Ono Equation

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 65
Author(s):  
Benjamin Akers ◽  
Tony Liu ◽  
Jonah Reeger
Keyword(s):  
Radial Basis Function ◽  
Hilbert Transform ◽  
Basis Function ◽  
Differential Operators ◽  
Convergence Rates ◽  
Traveling Wave Solutions ◽  
Algebraic Decay ◽  
Pseudo Differential Operators ◽  
Radial Basis ◽  
The Hilbert Transform

A radial basis function-finite differencing (RBF-FD) scheme was applied to the initial value problem of the Benjamin–Ono equation. The Benjamin–Ono equation has traveling wave solutions with algebraic decay and a nonlocal pseudo-differential operator, the Hilbert transform. When posed on R, the former makes Fourier collocation a poor discretization choice; the latter is challenging for any local method. We develop an RBF-FD approximation of the Hilbert transform, and discuss the challenges of implementing this and other pseudo-differential operators on unstructured grids. Numerical examples, simulation costs, convergence rates, and generalizations of this method are all discussed.

scholarly journals Phase Synchronization Is the Amplified Result by the Hilbert Transform

2015 ◽  
Vol 2015 ◽  
pp. 1-3 ◽  
Author(s):  
Ming-Chi Lu ◽  
Hsing-Chung Ho ◽  
Chen-An Chan ◽  
Chia-Ju Liu ◽  
Jiann-Shing Lih ◽  
...  
Keyword(s):  
Time Series ◽  
Dynamical Systems ◽  
Hilbert Transform ◽  
Phase Synchronization ◽  
Nonlinear Dynamical Systems ◽  
The State ◽  
Nonlinear Dynamical ◽  
Large Correlation ◽  
Current Usage ◽  
The Hilbert Transform

We investigate the interplay between phase synchronization and amplitude synchronization in nonlinear dynamical systems. It is numerically found that phase synchronization intends to be established earlier than amplitude synchronization. Nevertheless, amplitude synchronization (or the state with large correlation between the amplitudes) is crucial for the maintenance of a high correlation between two time series. A breakdown of high correlation in amplitudes will lead to a desynchronization of two time series. It is shown that these unique features are caused essentially by the Hilbert transform. This leads to a deep concern and criticism on the current usage of phase synchronization.

Additional Comments on "The Hilbert Transform as an Iterated Laplace Transform''

1968 ◽  
Vol AES-4 (5) ◽  
pp. 802-802
Author(s):  
J. T. Link ◽  
P. R. Hariharan ◽  
R. D. Schalow
Keyword(s):  
Laplace Transform ◽  
Hilbert Transform ◽  
The Hilbert Transform
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