As a classical and effective method for solving various time-varying problems, the zeroing
neural network (ZNN) is widely applied in the scientific and industrial realms. In plentiful …

A robust noise-tolerant zeroing neural network (ZNN) is introduced for solving time-varying
linear matrix equations (TVLME). The convergence speed of designed neural dynamics is …

The application of zeroing neural network (ZNN) to solve multifarious time-varying problems,
especially the dynamic matrix inversion (DMI), is widely used in recent years. As the core …

In the last decade, different multivariate statistical techniques have been applied to assist
enzymatic production by microorganisms through solid state fermentation (SSF). The …

Zeroing neural network has proved its powerful abilities and efficiency in solving various
time-varying problems, and its convergence and robustness have been deeply studied in …

An improved activation function, termed extended sign-bi-power (Esbp), is proposed. An
extension of the Li zeroing neural network (ELi-ZNN) based on the Esbp activation is …

Time-varying problems frequently arise in the territories of science and engineering, and
most of the time-varying problems can be described by dynamic matrix equations. As a …

Matrix inversion is commonly encountered in the field of mathematics. Therefore, many
methods, including zeroing neural network (ZNN), are proposed to solve matrix inversion …

Dynamic complex matrix inversion (DCMI) problems frequently arise in the territories of
mathematics and engineering, and various recurrent neural network (RNN) models have …

A family of zeroing neural networks based on new nonlinear activation functions is proposed
for solving various time-varying linear matrix equations (TVLME). The proposed neural …