Recent theoretical and empirical work on predictive processing and brain plasticity may help explain both the onset of and ...
Years of practice appeared to reshape the resting architecture of their minds. A passing state had, in some measure, become a ...
The team over at Waves must be feeling particularly generous this week, as the software developer announces that it's releasing a bundle of seven free plugins that features a convolution reverb, FM ...
Abstract: An approach to performing photonic-assisted temporal convolution of two microwave signals is proposed and experimentally demonstrated. Temporal convolution involves three operations: time ...
RF signals historically are measured using spectrum analyzers, at least that was before oscilloscopes offered sufficient bandwidth for those measurements. With oscilloscope bandwidths over 100 GHz, RF ...
Abstract: Convolutional dictionary learning (CDL) can represent signals and images via the superposition of components given by the convolution of sparse coefficients (features) and the elements of a ...
Diagnosis of shockable rhythms leading to defibrillation remains integral to improving out‐of‐hospital cardiac arrest outcomes. New machine learning techniques have emerged to diagnose arrhythmias on ...
The classification of electroencephalogram (EEG) signals is of significant importance in brain-computer interface (BCI) systems. Aiming to achieve intelligent classification of motor imagery EEG types ...
Deep Convolutional Neural Networks (DCNN) have the ability to learn complex features and are thus widely used in the field of seismic signal denoising with low signal-to-noise ratio (SNR). However, ...
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