AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Nonlinear Dynamics

Showing 71 to 80 of 745 articles

Clear Filters

Inverse-free zeroing neural network for time-variant nonlinear optimization with manipulator applications.

Neural networks : the official journal of the International Neural Network Society
In this paper, the problem of time-variant optimization subject to nonlinear equation constraint is studied. To solve the challenging problem, methods based on the neural networks, such as zeroing neural network and gradient neural network, are commo...

Deep learning-based low-dose CT simulator for non-linear reconstruction methods.

Medical physics
BACKGROUND: Computer algorithms that simulate lower-doses computed tomography (CT) images from clinical-dose images are widely available. However, most operate in the projection domain and assume access to the reconstruction method. Access to commerc...

Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network.

Biophysical reports
The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational prin...

Adaptive neural fault-tolerant prescribed performance control of a rehabilitation exoskeleton for lower limb passive training.

ISA transactions
This article studies the passive tracking problem of a wearable exoskeleton for lower limb rehabilitation therapy in the face of unmodeled dynamics, interactive friction, disturbance, prescribed performance constraints, and actuator faults. Adaptive ...

Adaptive sampling artificial-actual control for non-zero-sum games of constrained systems.

Neural networks : the official journal of the International Neural Network Society
Considering physical constraints encountered by actuators, this paper addresses the non-zero-sum game of continuous nonlinear systems with symmetric and asymmetric input constraints through aperiodic sampling artificial-actual control. Initially, the...

Heterogeneous coexisting attractors, large-scale amplitude control and finite-time synchronization of central cyclic memristive neural networks.

Neural networks : the official journal of the International Neural Network Society
Memristors are of great theoretical and practical significance for chaotic dynamics research of brain-like neural networks due to their excellent physical properties such as brain synapse-like memorability and nonlinearity, especially crucial for the...

Dynamics of heterogeneous Hopfield neural network with adaptive activation function based on memristor.

Neural networks : the official journal of the International Neural Network Society
Memristor and activation function are two important nonlinear factors of the memristive Hopfield neural network. The effects of different memristors on the dynamics of Hopfield neural networks have been studied by many researchers. However, less atte...

Advanced optimal tracking integrating a neural critic technique for asymmetric constrained zero-sum games.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the optimal tracking issue for continuous-time (CT) nonlinear asymmetric constrained zero-sum games (ZSGs) by exploiting the neural critic technique. Initially, an improved algorithm is constructed to tackle the tracking contr...

Tackling the curse of dimensionality with physics-informed neural networks.

Neural networks : the official journal of the International Neural Network Society
The curse-of-dimensionality taxes computational resources heavily with exponentially increasing computational cost as the dimension increases. This poses great challenges in solving high-dimensional partial differential equations (PDEs), as Richard E...