The study of the correlations that may exist between neurophysiological signals is at the heart of modern techniques for data analysis in neuroscience. Wavelet coherence is a popular method to construct a time-frequency map that can be used to analyze the time-frequency correlations between two time series. Coherence is a normalized measure of dependence, for which it is possible to construct c...

Background reverberation can obscure useful features of the target echo response in broadband low-frequency sonar images, adversely affecting detection and classification performance. This paper describes a resolution and phase-preserving means of separating the target response from the background reverberation noise using a coherence-based wavelet shrinkage method proposed recently for de-nois...

This paper describes the use of a computational tool based on the Morlet wavelet transform to investigate the interaction dynamics between oscillations generated by two anatomically distinct neuronal populations. The tool uses cross wavelet transform, coherence, bi-spectrum/bi-coherence and phase synchronization. Using specimen data recorded from the hippocampus of a rat with experimentally ind...

In this study, we propose a brain-computer interface (BCI) system to analyze single-trial electroencephalogram (EEG) signals. After the automatic EOG-artifact elimination, wavelet-coherence features and support vector machine (SVM) are adopted for the classification of left and right motor imagery (MI) data. EOG artifacts are removed automatically via modified independent component analysis (IC...

We thank the anonymous referee #1 for the positive and constructive remarks. Just like the referee, we struggled to improve and simplify the presentation of the technical results. In section 2 we tried to illustrate in a simple way the role of coherence by considering the (weak) pseudomaximal signals. Then, to justify the use of the wavelet transform, we showed how the coherence of phase inform...

The identification of image acquisition sources is an important problem in digital image forensics. This paper introduces a new feature-based method for digital camera identification. The method, which is based on an analysis of the imaging pipeline and digital camera processing operations, employs bi-coherence and wavelet coefficient features extracted from digital images. The sequential forwa...

Usual imaging process makes the assumption that the reflectors are isotropic (i.e they behave the same way regardless of the angle from which they are viewed) and white (they have the same properties within the emitted frequency bandwidth). New imaging capacities make these assumptions obsolete and some degradation of the image quality occurs when performing the standard imaging process. Multid...

This study examined whether interpersonal synchrony could be extracted using spectrum analysis (i.e., wavelet transform) in an unstructured conversation. Sixty-two female undergraduates were randomly paired and they engaged in a 6-min unstructured conversation. Interpersonal synchrony was evaluated by calculating the cross-wavelet coherence of the time-series movement data, extracted using a vi...

Wiener filter based postfiltering has shown its usefulness in microphone array speech enhancement systems. In our earlier work, we developed a postfilter in the wavelet domain where better performance has been obtained compared to the algorithms developed in the Fourier domain. Furthermore, considerable computational savings are provided thanks to the multi-resolution and multi-rate analysis. T...