Heart rate (HR) estimation and monitoring is of great importance to determine a person's
physiological and mental status. Recently, it has been demonstrated that HR can be …

An exhaustive review of adaptive signal processing schemes which are robust, sparsity-
aware and robust as well as sparsity-aware has been carried out in this paper. Conventional …

Traditional Kalman filter (KF) is derived under the well-known minimum mean square error
(MMSE) criterion, which is optimal under Gaussian assumption. However, when the signals …

Recently, wind speed forecasting as an effective computing technique plays an important
role in advancing industry informatics, while dealing with these issues of control and …

In this article, a statistical similarity measure is introduced to quantify the similarity between
two random vectors. The measure is, then, employed to develop a novel outlier-robust …

Short-term traffic flow forecasting at isolated points is a fundamental yet challenging task in
many intelligent transportation systems. We present a novel long short-term memory (LSTM) …

The applications of error entropy (EE) are sometimes limited because its shape cannot be
flexibly adjusted by the default Gaussian kernel function to adapt to noise variation and thus …

Correntropy is a local similarity measure defined in kernel space, hence can combat large
outliers in robust signal processing and machine learning. So far, many robust learning …

A blocked proportionate normalized maximum correntropy criterion (PNMCC) is presented
to improve the estimation behavior of the traditional maximum correntropy criterion (MCC) …

In recent years, correntropy-based algorithms which include maximum correntropy criterion
(MCC), generalized MCC (GMCC), kernel MCC (KMCC) and hyperbolic cosine function …