<p>The Hilbert transform is a phase shifter, which represents the complex complement
to a real vauled signal. It is calculated in the complex frequency space of the
signal by using the Fourier transform. Finally, calculating \(f = y + i*H(y)\)
gives the analytic signal, with a one sided spectrum. (See <code><a rd-options="" href="/link/analyticFunction?package=spectral&version=2.0" data-mini-rdoc="spectral::analyticFunction">analyticFunction</a></code>)</p>

On discrete data spectral analysis is performed by Fourier and Hilbert
transforms as well as with model based analysis called Lomb-Scargle method.
Fragmented and irregularly spaced data can be processed in almost all methods. Both,
FFT as well as LOMB methods take multivariate data and return standardized PSD.
For didactic reasons an analytical approach for deconvolution of noise spectra and
sampling function is provided.
A user friendly interface helps to interpret the results.

Martin Seilmayer

spectral

Common Methods of Spectral Data Analysis

H function

<p>The Hilbert transform is a phase shifter, which represents the complex complement
to a real vauled signal. It is calculated in the complex frequency space of the
signal by using the Fourier transform. Finally, calculating \(f = y + i*H(y)\)
gives the analytic signal, with a one sided spectrum. (See <code><a rd-options='' href='analyticFunction'>analyticFunction</a></code>)</p>

H: The Hilbert transformation

Description

Usage

Arguments

Value