Convolutional neural networks (CNNs) have been commonly applied in the area of Electroencephalography (EEG)-based Motor Imagery (MI) classification, significantly pushing boundary state-of-the-art. In order to simultaneously decode discriminative features and eliminate negative effects non-Gaussian noise outliers motor imagery data, this abstract, we propose a novel robust supervision signal, c...

Forecasting the particulate matter (PM) concentration in South Korea has become urgently necessary owing to its strong negative impact on human life. In most statistical or machine learning methods, independent and identically distributed data, for example, a Gaussian distribution, are assumed; however, time series such as air pollution weather data do not meet this assumption. study, maximum c...

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical s...

Suppression of noise and artifacts is a necessary step in biomedical data processing. Adaptive filtering is known as useful method to overcome this problem. Among various contaminants, there are some situations such as electrical activities of muscles contribute to impulsive noise. This paper deals with modeling real-life muscle noise with α-stable probability distribution and adaptive filterin...

In the leader–follower-based multiple underwater unmanned vehicles (UUVs) cooperative positioning system, precision of compass and Doppler velocity log equipped with follower UUV is low, which will inevitably lead to yaw error (YEaVE) in output data. These errors seriously affect accuracy UUV. addition, observation information often has many outliers due influence multipath, cause increase erro...

We propose an approach for the synchronization of video streams using correntropy. Essentially, the time offset is calculated on the basis of the instantaneous transfer rates of the video streams that are extracted in the form of a univariate signal known as variable bit-rate (VBR). The state-of-the-art approach uses a window segmentation strategy that is based on consensual zero-mean normalize...

Communication systems are affected by channel distortions. Impulsive noise is one of the significant factors for impairments. The standard additive white Gaussian (AWGN) model and conventional estimation algorithms like least mean square (LMS) its variants tend to be ineffective under such conditions. This paper presents a robust adaptive algorithm using Geman-McClure estimator in diffusion-bas...