Gradient-based differential neural-solution to time-dependent nonlinear optimization
In this technical article, to seek the optimal solution to time-dependent nonlinear optimization
subject to linear inequality and equality constraints (TDNO-IEC), the gradient-based …
subject to linear inequality and equality constraints (TDNO-IEC), the gradient-based …
Dynamic neural network models for time-varying problem solving: a survey on model structures
C Hua, X Cao, Q Xu, B Liao, S Li - IEEE Access, 2023 - ieeexplore.ieee.org
In recent years, neural networks have become a common practice in academia for handling
complex problems. Numerous studies have indicated that complex problems can generally …
complex problems. Numerous studies have indicated that complex problems can generally …
Double integral‐enhanced Zeroing neural network with linear noise rejection for time‐varying matrix inverse
B Liao, L Han, X Cao, S Li, J Li - CAAI Transactions on …, 2024 - Wiley Online Library
In engineering fields, time‐varying matrix inversion (TVMI) issue is often encountered.
Zeroing neural network (ZNN) has been extensively employed to resolve the TVMI problem …
Zeroing neural network (ZNN) has been extensively employed to resolve the TVMI problem …
GNN model for time-varying matrix inversion with robust finite-time convergence
As a type of recurrent neural networks (RNNs) modeled as dynamic systems, the gradient
neural network (GNN) is recognized as an effective method for static matrix inversion with …
neural network (GNN) is recognized as an effective method for static matrix inversion with …
Exploiting the Black-Litterman framework through error-correction neural networks
Abstract The Black-Litterman (BL) model is a particularly essential analytical tool for effective
portfolio management in financial services sector since it enables investment analysts to …
portfolio management in financial services sector since it enables investment analysts to …
Inter-robot management via neighboring robot sensing and measurement using a zeroing neural dynamics approach
B Liao, C Hua, Q Xu, X Cao, S Li - Expert Systems with Applications, 2024 - Elsevier
This paper proposes a complex number representation method for dynamically recording
robot positions and develops an optimization strategy for measuring and minimizing inter …
robot positions and develops an optimization strategy for measuring and minimizing inter …
Solving time-varying nonsymmetric algebraic Riccati equations with zeroing neural dynamics
The problem of solving algebraic Riccati equations (AREs) and certain linear matrix
equations which arise from the ARE frequently occur in applied and pure mathematics …
equations which arise from the ARE frequently occur in applied and pure mathematics …
A higher-order zeroing neural network for pseudoinversion of an arbitrary time-varying matrix with applications to mobile object localization
The hyperpower family of iterative methods with arbitrary convergence order is one of the
most used methods for estimating matrix inverses and generalized inverses, whereas the …
most used methods for estimating matrix inverses and generalized inverses, whereas the …
Unique non-negative definite solution of the time-varying algebraic Riccati equations with applications to stabilization of LTV systems
In the context of infinite-horizon optimal control problems, the algebraic Riccati equations
(ARE) arise when the stability of linear time-varying (LTV) systems is investigated. Using the …
(ARE) arise when the stability of linear time-varying (LTV) systems is investigated. Using the …
Zeroing neural network for pseudoinversion of an arbitrary time-varying matrix based on singular value decomposition
M Kornilova, V Kovalnogov, R Fedorov, M Zamaleev… - Mathematics, 2022 - mdpi.com
Many researchers have investigated the time-varying (TV) matrix pseudoinverse problem in
recent years, for its importance in addressing TV problems in science and engineering. In …
recent years, for its importance in addressing TV problems in science and engineering. In …