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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...

Improving the performance of echo state networks through state feedback.

Neural networks : the official journal of the International Neural Network Society
Reservoir computing, using nonlinear dynamical systems, offers a cost-effective alternative to neural networks for complex tasks involving processing of sequential data, time series modeling, and system identification. Echo state networks (ESNs), a t...

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...

CDCG-UNet: Chaotic Optimization Assisted Brain Tumor Segmentation Based on Dilated Channel Gate Attention U-Net Model.

Neuroinformatics
Brain tumours are one of the most deadly and noticeable types of cancer, affecting both children and adults. One of the major drawbacks in brain tumour identification is the late diagnosis and high cost of brain tumour-detecting devices. Most existin...

Nonlinear feature selection for support vector quantile regression.

Neural networks : the official journal of the International Neural Network Society
This paper discusses the nuanced domain of nonlinear feature selection in heterogeneous systems. To address this challenge, we present a sparsity-driven methodology, namely nonlinear feature selection for support vector quantile regression (NFS-SVQR)...

A smooth gradient approximation neural network for general constrained nonsmooth nonconvex optimization problems.

Neural networks : the official journal of the International Neural Network Society
Nonsmooth nonconvex optimization problems are pivotal in engineering practice due to the inherent nonsmooth and nonconvex characteristics of many real-world complex systems and models. The nonsmoothness and nonconvexity of the objective and constrain...

EEG Signals Classification Related to Visual Objects Using Long Short-Term Memory Network and Nonlinear Interval Type-2 Fuzzy Regression.

Brain topography
By gaining insights into how brain activity is encoded and decoded, we enhance our understanding of brain function. This study introduces a method for classifying EEG signals related to visual objects, employing a combination of an LSTM network and n...