AIMC Topic: Nonlinear Dynamics

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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...

Multi-level feature interaction image super-resolution network based on convolutional nonlinear spiking neural model.

Neural networks : the official journal of the International Neural Network Society
Image super-resolution (ISR) is designed to recover lost detail information from low-resolution images, resulting in high-quality and high-definition high-resolution images. In the existing single ISR (SISR) methods based on convolutional neural netw...

Neural critic learning with accelerated value iteration for nonlinear model predictive control.

Neural networks : the official journal of the International Neural Network Society
In practical industrial processes, the receding optimization solution of nonlinear model predictive control (NMPC) is always a very knotty problem. Based on adaptive dynamic programming, the accelerated value iteration predictive control (AVI-PC) alg...

LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data.

Neural networks : the official journal of the International Neural Network Society
Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential equations (PDE). However, it requires a large amo...

Modelling for disability: How does artificial intelligence affect unemployment among people with disability? An empirical analysis of linear and nonlinear effects.

Research in developmental disabilities
There is a growing debate among scholars regarding the impact of artificial intelligence (AI) on the employment opportunities and professional development of people with disability. Although there has been an increasing body of empirical research on ...

Multitask Adversarial Networks Based on Extensive Nonlinear Spiking Neuron Models.

International journal of neural systems
Deep learning technology has been successfully used in Chest X-ray (CXR) images of COVID-19 patients. However, due to the characteristics of COVID-19 pneumonia and X-ray imaging, the deep learning methods still face many challenges, such as lower ima...