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 …

Predictive modeling in medicine involves the development of computational models which
are capable of analysing large amounts of data in order to predict healthcare outcomes for …

The fixed-time synchronization and preassigned-time synchronization of quaternion-valued
neural networks are concerned in this article. By develo** fixed-time stability and …

In this paper, we investigate the global stability of quaternion-valued neural networks
(QVNNs) with time-varying delays. On one hand, in order to avoid the noncommutativity of …

Second order statistics of quaternion random variables and signals are revisited in order to
exploit the complete second order statistical information available. The conditions for Q …

An extension of empirical mode decomposition (EMD) is proposed in order to make it
suitable for operation on trivariate signals. Estimation of local mean envelope of the input …

In this paper, a new type of neural networks, quaternion-valued memristive neural networks
(QVMNNs) is formulated. On the basis of the differential inclusion principle and the …

The digital twin of the ocean (DTO) is a groundbreaking concept that uses interactive
simulations to improve decision-making and promote sustainability in earth science. The …

Real functions of quaternion variables are typical cost functions in quaternion valued
statistical signal processing, however, standard differentiability conditions in the quaternion …

A class of nonlinear quaternion-valued adaptive filtering algorithms is proposed based on
locally analytic nonlinear activation functions. To circumvent the stringent standard …