BACKGROUND Continuous and discrete wavelet transforms have been established as valid tools to analyze non-stationary and transient signals over Fourier domain methods. Additionally, Fourier transform based coherence methods provide aggregate results but do not provide insights into the changes in coherent behavior over time, hence limiting their utility. METHODS Statistical validation of the ...

Recently, the authors presented an EEG (electroencephalogram) coherence study of the Alzheimer's disease (AD) and found statistically significant differences between AD and control groups. In this paper a probabilistic neural network (PNN) model is presented for classification of AD and healthy controls using features extracted in coherence and wavelet coherence studies on cortical connectivity...

Humans are able to detect blurring of visual images, but the mechanism by which they do so is not clear. A traditional view is that a blurred image looks “unnatural” because of the reduction in energy (either globally or locally) at high frequencies. In this paper, we propose that the disruption of local phase can provide an alternative explanation for blur perception. We show that precisely lo...

In order to detect intermittent firstand higher-order correlation between a pair of signals in both time and frequency, a wavelet-based coherence and bicoherence technique was developed. Due to the limited averaging in a time-frequency coherence estimate, spurious correlated pockets were detected due to statistical variance. The introduction of multiresolution, localized integration windows was...

The continuous wavelet transform (CWT) is specifically efficient in the analysis of transient and non-stationary signals. As such, it has become a powerful candidate for time-frequency analysis of cardiovascular variability. CWT has already been established as a valid tool for the analysis of single cardiovascular signals, providing additional insights into the autonomous nervous system (ANS) a...

This study analysed the influence of ongoing Russia–Ukraine war on US oil prices. The quantile regression estimates revealed that increased wavelet coherence analysis also played a key role in suggested policies reduced prices, such as transition towards renewable energy sources and provision government incentives, to minimize impact war.

Abstract Several studies have examined the implications of different macroeconomics variables on energy consumption, but findings been mixed, in addition, study context Egypt scant literature. Thus, our investigates economic growth, gross capital formation, urbanization, and import as determinants consumption using a time series from 1971 to 2017, employed wavelet coherent technique for analysi...