AIMC Topic: Computer Simulation

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Delay-Dependent Switching Approaches for Stability Analysis of Two Additive Time-Varying Delay Neural Networks.

IEEE transactions on neural networks and learning systems
This article analyzes the exponentially stable problem of neural networks (NNs) with two additive time-varying delay components. Disparate from the previous solutions on this similar model, switching ideas, that divide the time-varying delay interval...

IBLF-Based Adaptive Neural Control of State-Constrained Uncertain Stochastic Nonlinear Systems.

IEEE transactions on neural networks and learning systems
In this article, the adaptive neural backstepping control approaches are designed for uncertain stochastic nonlinear systems with full-state constraints. According to the symmetry of constraint boundary, two cases of controlled systems subject to sym...

Prescribed Finite-Time Adaptive Neural Tracking Control for Nonlinear State-Constrained Systems: Barrier Function Approach.

IEEE transactions on neural networks and learning systems
The purpose of this article is to present a novel backstepping-based adaptive neural tracking control design procedure for nonlinear systems with time-varying state constraints. The designed adaptive neural tracking controller is expected to have the...

Evaluating the statistical similarity of neural network activity and connectivity via eigenvector angles.

Bio Systems
Neural systems are networks, and strategic comparisons between multiple networks are a prevalent task in many research scenarios. In this study, we construct a statistical test for the comparison of matrices representing pairwise aspects of neural ne...

Machine Learning-Based Air-to-Ground Channel Model Selection Method for UAV Communications Using Digital Surface Model Data.

Sensors (Basel, Switzerland)
This paper proposes an automatic air-to-ground (A2G) channel model selection method based on machine learning (ML) using digital surface model (DSM) terrain data. In order to verify whether a communication network for a new non-terrestrial user servi...

A Sampling-Based Algorithm with the Metropolis Acceptance Criterion for Robot Motion Planning.

Sensors (Basel, Switzerland)
Motion planning is one of the important research topics of robotics. As an improvement of Rapidly exploring Random Tree (RRT), the RRT* motion planning algorithm is widely used because of its asymptotic optimality. However, the running time of RRT* i...

No need to forget, just keep the balance: Hebbian neural networks for statistical learning.

Cognition
Language processing in humans has long been proposed to rely on sophisticated learning abilities including statistical learning. Endress and Johnson (E&J, 2021) recently presented a neural network model for statistical learning based on Hebbian learn...

Deep Learning-Based Framework for Fast and Accurate Acoustic Hologram Generation.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and medical imaging. However, only a few studies on how to generate acoustic holograms have been conducted...

Ultrasound Imaging With a Flexible Probe Based on Element Array Geometry Estimation Using Deep Neural Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Conventionally, ultrasound (US) diagnosis is performed using hand-held rigid probes. Such devices are difficult to be used for long-term monitoring because they need to be continuously pressed against the body to remove the air between the probe and ...

Coordinated Navigation of Two Agricultural Robots in a Vineyard: A Simulation Study.

Sensors (Basel, Switzerland)
The development of an effective agricultural robot presents various challenges in actuation, localization, navigation, sensing, etc., depending on the prescribed task. Moreover, when multiple robots are engaged in an agricultural task, this requires ...