Related Experiment Video
Updated: Jun 6, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
Published on: September 3, 2021
Analysis of Magnetic Resonance Spectroscopic signals with data-based autocorrelation wavelets
A Schuck1, C Lemke, A Suvichakorn
1Electrical Eng. Dept. (DELET), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. adalberto.schuck@uclouvain.be
Abstract:
A new class of wavelet functions called data-based autocorrelation wavelets is developed for analyzing Magnetic Resonance Spectroscopic (MRS) signals by means of the continuous wavelet transform (CWT), instead of the traditional wavelet like Morlet wavelet. These new wavelets are derived from the normalized autocorrelation function from metabolite data and then used for detecting the presence of a given metabolite in a signal with a presence of many different components and finally for quantifying some of its parameters.
Related Concept Videos
2D NMR: Overview of Heteronuclear Correlation Techniques
2D NMR: Overview of Homonuclear Correlation Techniques
COSY90 is the standard two-dimensional (2D) COSY experiment that...
¹H NMR: Interpreting Distorted and Overlapping Signals
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
2D NMR: Homonuclear Correlation Spectroscopy (COSY)
¹H NMR Signal Multiplicity: Splitting Patterns
2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

