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Nonlinear Dynamics

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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...

A symbolic network-based nonlinear theory for dynamical systems observability.

Scientific reports
When the state of the whole reaction network can be inferred by just measuring the dynamics of a limited set of nodes the system is said to be fully observable. However, as the number of all possible combinations of measured variables and time deriva...

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

Neural networks : the official journal of the International Neural Network Society
The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive cri...

Design of nonlinear optimal control for chaotic synchronization of coupled stochastic neural networks via Hamilton-Jacobi-Bellman equation.

Neural networks : the official journal of the International Neural Network Society
This paper presents a new theoretical design of nonlinear optimal control on achieving chaotic synchronization for coupled stochastic neural networks. To obtain an optimal control law, the proposed approach is developed rigorously by using Hamilton-J...

Globally fixed-time synchronization of coupled neutral-type neural network with mixed time-varying delays.

PloS one
This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network mode...

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, o...