AI Medical Compendium Topic

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

Nonlinear Dynamics

Showing 61 to 70 of 745 articles

Clear Filters

A novel fractional-order memristive Hopfield neural network for traveling salesman problem and its FPGA implementation.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a novel fractional-order memristive Hopfield neural network (HNN) to address traveling salesman problem (TSP). Fractional-order memristive HNN can efficiently converge to a globally optimal solution, while conventional HNN tends t...

Photonic deep residual time-delay reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Time-delay reservoir computing (TDRC) represents a simplified variant of recurrent neural networks, employing a nonlinear node with a feedback mechanism to construct virtual nodes. The capabilities of TDRC can be enhanced by transitioning to a deep a...

CAPE: a deep learning framework with Chaos-Attention net for Promoter Evolution.

Briefings in bioinformatics
Predicting the strength of promoters and guiding their directed evolution is a crucial task in synthetic biology. This approach significantly reduces the experimental costs in conventional promoter engineering. Previous studies employing machine lear...

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. S...

Prescribed performance adaptive neural event-triggered control for switched nonlinear cyber-physical systems under deception attacks.

Neural networks : the official journal of the International Neural Network Society
In this paper, the design of an adaptive neural event-triggered control scheme for a class of switched nonlinear systems affected by external disturbances and deception attacks is presented. In order to address the effects caused by unknown disturban...

Optimal synchronization with L-gain performance: An adaptive dynamic programming approach.

Neural networks : the official journal of the International Neural Network Society
This paper studies an optimal synchronous control protocol design for nonlinear multi-agent systems under partially known dynamics and uncertain external disturbance. Under some mild assumptions, Hamilton-Jacobi-Isaacs equation is derived by the perf...

Stability and synchronization of fractional-order reaction-diffusion inertial time-delayed neural networks with parameters perturbation.

Neural networks : the official journal of the International Neural Network Society
This study is centered around the dynamic behaviors observed in a class of fractional-order generalized reaction-diffusion inertial neural networks (FGRDINNs) with time delays. These networks are characterized by differential equations involving two ...

Finite-time cluster synchronization of multi-weighted fractional-order coupled neural networks with and without impulsive effects.

Neural networks : the official journal of the International Neural Network Society
In this paper, finite-time cluster synchronization (FTCS) of multi-weighted fractional-order neural networks is studied. Firstly, a FTCS criterion of the considered neural networks is obtained by designing a new delayed state feedback controller. Sec...

Bayesian learning of feature spaces for multitask regression.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a novel approach to learn multi-task regression models with constrained architecture complexity. The proposed model, named RFF-BLR, consists of a randomised feedforward neural network with two fundamental characteristics: a sing...

How Can Anomalous-Diffusion Neural Networks Under Connectomics Generate Optimized Spatiotemporal Dynamics.

IEEE transactions on neural networks and learning systems
Spatiotemporal dynamics in the brain have been recognized as strongly related to the formation of perceived and cognitive diseases, such as delusions and hallucinations in Alzheimer's disease. However, two practical considerations are rarely mentione...