AIMC Topic: Nonlinear Dynamics

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Fault diagnosis of nonlinear analog circuits using generalized frequency response function and LSSVM.

PloS one
A fault diagnosis method of nonlinear analog circuits is proposed that combines the generalized frequency response function (GFRF) and the simplified least squares support vector machine (LSSVM). In this study, the harmonic signal is used as an input...

Chaotic recurrent neural networks for brain modelling: A review.

Neural networks : the official journal of the International Neural Network Society
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous ac...

Neural network-based dynamic target enclosing control for uncertain nonlinear multi-agent systems over signed networks.

Neural networks : the official journal of the International Neural Network Society
Neural networks have significant advantages in the estimation of uncertainty dynamics, which can afford highly accurate prediction outcomes and enhance control robustness. With this in mind, this study presents a neural network-based method to invest...

Accelerated quadratic penalty dynamic approaches with applications to distributed optimization.

Neural networks : the official journal of the International Neural Network Society
In this paper, we explore accelerated continuous-time dynamic approaches with a vanishing damping α/t, driven by a quadratic penalty function designed for linearly constrained convex optimization problems. We replace these linear constraints with pen...

Adaptive discrete-time neural prescribed performance control: A safe control approach.

Neural networks : the official journal of the International Neural Network Society
Most existing results on prescribed performance control (PPC), subject to input saturation and initial condition limitations, focus on continuous-time nonlinear systems. This article, as regards discrete-time nonlinear systems, is dedicated to constr...

A simple remedy for failure modes in physics informed neural networks.

Neural networks : the official journal of the International Neural Network Society
Physics-informed neural networks (PINNs) have shown promising results in solving a wide range of problems involving partial differential equations (PDEs). Nevertheless, there are several instances of the failure of PINNs when PDEs become more complex...

Super-fast and accurate nonlinear foot deformation Prediction using graph neural networks.

Journal of the mechanical behavior of biomedical materials
Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized insoles, tailored to an individual's foot morphology, have emerged as a promising solution. However, th...

Enhancing green supplier selection: A nonlinear programming method with TOPSIS in cubic Pythagorean fuzzy contexts.

PloS one
The advancements in information and communication technologies have given rise to innovative developments such as cloud computing, the Internet of Things, big data analytics, and artificial intelligence. These technologies have been integrated into p...

Event-based adaptive fixed-time optimal control for saturated fault-tolerant nonlinear multiagent systems via reinforcement learning algorithm.

Neural networks : the official journal of the International Neural Network Society
This article investigates the problem of adaptive fixed-time optimal consensus tracking control for nonlinear multiagent systems (MASs) affected by actuator faults and input saturation. To achieve optimal control, reinforcement learning (RL) algorith...

A non-linear modelling approach to predict the dissolution profile of extended-release tablets.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This study proposes a novel non-linear modelling approach to predict the dissolution profiles of extended-release tablets, by combining a full-factorial design, curve fitting to the dissolution profiles, and artificial neural networks (ANN), with lin...