Neurodynamic optimization approaches with finite/fixed-time convergence for absolute value equations

Cites Work

Unnamed Item
Unsupervised and semisupervised classification via absolute value inequalities
On the global convergence of the inexact semi-smooth Newton method for absolute value equation
A dynamic model to solve the absolute value equations
Absolute value equations
Neural network based on systematically generated smoothing functions for absolute value equation
An inverse-free dynamical system for solving the absolute value equations
Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks
A new noise-tolerant and predefined-time ZNN model for time-dependent matrix inversion
On the SOR-like iteration method for solving absolute value equations
On equivalent reformulations for absolute value equations
An inertial inverse-free dynamical system for solving absolute value equations
Fixed-Time Synchronization of Complex Networks With Impulsive Effects via Nonchattering Control
A variational perspective on accelerated methods in optimization
Finite-Time Stability of Continuous Autonomous Systems
Fixed-Time Stable Gradient Flows: Applications to Continuous-Time Optimization
Nonlinear Feedback Design for Fixed-Time Stabilization of Linear Control Systems
A neurodynamic approach for nonsmooth optimal power consumption of intelligent and connected vehicles
A one-layer recurrent neural network for nonsmooth pseudoconvex optimization with quasiconvex inequality and affine equality constraints
Novel projection neurodynamic approaches for constrained convex optimization
Fixed-time synchronization of discontinuous competitive neural networks with time-varying delays
Neurodynamics-driven portfolio optimization with targeted performance criteria

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