Common Methods of Spectral Data Analysis
Local Maxima
Analytic function
Simple bandpass function
Deconvolve Sampling Spectrum for Equidistant Sampling
Calculates the envelope of a band limited signal
Filter in the frequency domain
Filter and reconstruction of data analysed via spec.lomb
generalized Lomb-Scargle estimation function
The Hilbert transformation
interpolates data using the Fourier back transform
Lomb-Scargle estimation function
Setting up multithread BLAS library
Reset multithread BLAS to default
Plot fft-objects
plot method for Lomb-Scargle periodograms
FFT-Plotting Function
Lomb-Plotting Function
1D/2D/nD (multivariate) spectrum of the Fourier transform
Lomb-Scargle Periodigram
Summarize FFT objects
Summarize Lomb objects
Estimate the local frequencies
Cosine window function
Hanning window function
Nuttall window function
Tukey window function
Windowfunctions
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.