Characterization of the stability range of the Hilbert transform with applications to spectral factorization

2017 ◽  
Author(s):  
Holger Boche ◽  
Volker Pohl
Keyword(s):  
Hilbert Transform ◽  
Spectral Factorization ◽  
Stability Range ◽  
The Stability ◽  
The Hilbert Transform

scholarly journals A characterization of the Hilbert transform

1998 ◽  
Vol 126 (6) ◽  
pp. 1747-1749
Author(s):  
Nicola Arcozzi ◽  
Luigi Fontana
Keyword(s):  
Hilbert Transform ◽  
The Hilbert Transform

Non-Parametric Identification of Asymmetric Signals and Characterization of a Class of Non-Linear Systems Based on Frequency Modulation

2016 ◽  
Author(s):  
Václav Ondra ◽  
Ibrahim A. Sever ◽  
Christoph W. Schwingshackl
Keyword(s):  
Linear Systems ◽  
Hilbert Transform ◽  
Frequency Modulation ◽  
Parametric Identification ◽  
Free Decay ◽  
Non Linear ◽  
Non Linear Systems ◽  
The Hilbert Transform ◽  
Non Parametric

Non-parametric and parametric identification of a non-linear system is often performed by estimating instantaneous amplitude and frequency using the Hilbert transform. However, the Hilbert transform cannot be used for the accurate analysis of asymmetric signals and the reliable estimation of intra-wave frequency modulation. This paper proposes two alternatives to the Hilbert transform which not only avoid some of its mathematical and numerical issues, but also allow the above mentioned analyses. The first method, based on zero-crossing, allows the backbone and damping curves as well as the elastic and damping force characteristics of an asymmetric free decay to be identified. The application and accuracy of this method are demonstrated on the free decay of the system with off-centre clearance. The second method, based on direct quadrature, estimates intrawave frequency modulation frequency with sufficient resolution for characterization of non-linear systems which have stiffness non-linearities. The use of this method is shown on a system with cubic hardening stiffness.

TEM characterization of Au/Polysilicon interactions

1990 ◽  
Vol 48 (4) ◽  
pp. 650-651
Author(s):  
N. David Theodore ◽  
Leslie H. Allen ◽  
C. Barry Carter ◽  
James W. Mayer
Keyword(s):  
Solid Phase ◽  
Single Crystal Silicon ◽  
Chemical Vapor ◽  
Electrical Contacts ◽  
Silicon Substrates ◽  
Crystal Silicon ◽  
Transmission Electron ◽  
Polysilicon Films ◽  
The Stability

Metal/polysilicon investigations contribute to an understanding of issues relevant to the stability of electrical contacts in semiconductor devices. These investigations also contribute to an understanding of Si lateral solid-phase epitactic growth. Metals such as Au, Al and Ag form eutectics with Si. reactions in these metal/polysilicon systems lead to the formation of large-grain silicon. Of these systems, the Al/polysilicon system has been most extensively studied. In this study, the behavior upon thermal annealing of Au/polysilicon bilayers is investigated using cross-section transmission electron microscopy (XTEM). The unique feature of this system is that silicon grain-growth occurs at particularly low temperatures ∽300°C).Gold/polysilicon bilayers were fabricated on thermally oxidized single-crystal silicon substrates. Lowpressure chemical vapor deposition (LPCVD) at 620°C was used to obtain 100 to 400 nm polysilicon films. The surface of the polysilicon was cleaned with a buffered hydrofluoric acid solution. Gold was then thermally evaporated onto the samples.

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>

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