AIMC Topic: Nonlinear Dynamics

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Response prediction of nonlinear hysteretic systems by deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Nonlinear hysteretic systems are common in many engineering problems. The maximum response estimation of a nonlinear hysteretic system under stochastic excitations is an important task for designing and maintaining such systems. Although a nonlinear ...

Perceptual Decision-Making: Biases in Post-Error Reaction Times Explained by Attractor Network Dynamics.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Perceptual decision-making is the subject of many experimental and theoretical studies. Most modeling analyses are based on statistical processes of accumulation of evidence. In contrast, very few works confront attractor network models' predictions ...

Fixed Points of Competitive Threshold-Linear Networks.

Neural computation
Threshold-linear networks (TLNs) are models of neural networks that consist of simple, perceptron-like neurons and exhibit nonlinear dynamics determined by the network's connectivity. The fixed points of a TLN, including both stable and unstable equi...

A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects.

Medical & biological engineering & computing
This paper presents a unified approach based on the recurrence quantification analysis (RQA) and approximate entropy (ApEn) for the classification of heart rate variability (HRV). In this paper, the optimum tolerance threshold (r) corresponding to Ap...

Structural, dynamical and symbolic observability: From dynamical systems to networks.

PloS one
Classical definitions of observability classify a system as either being observable or not. Observability has been recognized as an important feature to study complex networks, and as for dynamical systems the focus has been on determining conditions...

A neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints. The proposed neural network endows with a time-varying auxiliary function, which can guarantee that the state of th...

Deep active inference.

Biological cybernetics
This work combines the free energy principle and the ensuing active inference dynamics with recent advances in variational inference in deep generative models, and evolution strategies to introduce the "deep active inference" agent. This agent minimi...

Control of a muscle-like soft actuator via a bioinspired approach.

Bioinspiration & biomimetics
Soft actuators have played an indispensable role in generating compliant motions of soft robots. Among the various soft actuators explored for soft robotic applications, dielectric elastomer actuators (DEAs) have caught the eye with their intriguing ...

Early Expression Detection via Online Multi-Instance Learning With Nonlinear Extension.

IEEE transactions on neural networks and learning systems
Video-based facial expression recognition has received substantial attention over the past decade, while early expression detection (EED) is still a relatively new and challenging problem. The goal of EED is to identify an expression as quickly as po...

Neighborhood preserving neural network for fault detection.

Neural networks : the official journal of the International Neural Network Society
A novel statistical feature extraction method, called the neighborhood preserving neural network (NPNN), is proposed in this paper. NPNN can be viewed as a nonlinear data-driven fault detection technique through preserving the local geometrical struc...