AIMC Topic: Nonlinear Dynamics

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Adaptive Neural Control of Pure-Feedback Nonlinear Systems With Event-Triggered Communications.

IEEE transactions on neural networks and learning systems
This paper is concerned with the adaptive event-triggered control problem for a class of pure-feedback nonlinear systems. Unlike the existing results where the control execution is periodic, the new proposed scheme updates the controller and the neur...

Dynamical and Static Multisynchronization of Coupled Multistable Neural Networks via Impulsive Control.

IEEE transactions on neural networks and learning systems
This paper investigates the dynamical multisynchronization and static multisynchronization problem for delayed coupled multistable neural networks with fixed and switching topologies. To begin with, a class of activation functions as well as several ...

A Reinforcement Learning Neural Network for Robotic Manipulator Control.

Neural computation
We propose a neural network model for reinforcement learning to control a robotic manipulator with unknown parameters and dead zones. The model is composed of three networks. The state of the robotic manipulator is predicted by the state network of t...

Practical Time-Varying Formation Tracking for Second-Order Nonlinear Multiagent Systems With Multiple Leaders Using Adaptive Neural Networks.

IEEE transactions on neural networks and learning systems
Practical time-varying formation tracking problems for second-order nonlinear multiagent systems with multiple leaders are investigated using adaptive neural networks (NNs), where the time-varying formation tracking error caused by time-varying exter...

Bio-inspired spiking neural network for nonlinear systems control.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more co...

Deformable Image Registration Using a Cue-Aware Deep Regression Network.

IEEE transactions on bio-medical engineering
SIGNIFICANCE: Analysis of modern large-scale, multicenter or diseased data requires deformable registration algorithms that can cope with data of diverse nature.

General memristor with applications in multilayer neural networks.

Neural networks : the official journal of the International Neural Network Society
Memristor describes the relationship between charge and flux. Although several window functions for memristors based on the HP linear and nonlinear dopant drift models have been studied, most of them are inadequate to capture the full characteristics...

Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels.

IEEE transactions on medical imaging
This paper introduces a fast, general method for dictionary-free parameter estimation in quantitative magnetic resonance imaging (QMRI) parameter estimation via regression with kernels (PERK). PERK first uses prior distributions and the nonlinear MR ...

Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller.

Neural networks : the official journal of the International Neural Network Society
The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equa...

Age-related changes in the ease of dynamical transitions in human brain activity.

Human brain mapping
Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural system...