Pulse-coupled neural networks (PCNN) have an inherent ability to process the signals
associated with the digital visual images because it is inspired from the neuronal activity in …

The Brain's ability to integrate information from different modalities (multisensory integration)
is fundamental for accurate sensory experience and efficient interaction with the …

Abstract Background and Objective Despite many models have been proposed for brain
visual perception and content understanding via electroencephalograms (EEGs), due to the …

This paper proposes an automated visual classification framework in which a novel analysis
method (LSTMS-B) of EEG signals guides the selection of multiple networks that leads to the …

In this paper, the state estimation problem is investigated for a class of discrete time-delay
nonlinear complex networks with randomly occurring phenomena from sensor …

In this paper, a novel view invariant action recognition method based on neural network
representation and recognition is proposed. The novel representation of action videos is …

Gamma activity has been linked to a variety of different cognitive processes and exists in
both transient and persistent forms. Across studies, different brain regions have been …

Background The role of sleep in cognitive processes has been confirmed by a growing
number of reports for all ages of life. Analysing sleep electroencephalogram (EEG) spectra …

Recently, experimental and theoretical research has focused on the brain's abilities to
extract information from a noisy sensory environment and how cross‐modal inputs are …

Background As a physiological signal, EEG data cannot be subjectively changed or hidden.
Compared with other physiological signals, EEG signals are directly related to human …