AIMC Topic: Computer Simulation

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Gossip-based distributed stochastic mirror descent for constrained optimization.

Neural networks : the official journal of the International Neural Network Society
This paper considers a distributed constrained optimization problem over a multi-agent network in the non-Euclidean sense. The gossip protocol is adopted to relieve the communication burden, which also adapts to the constantly changing topology of th...

Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust.

IEEE transactions on neural networks and learning systems
The first step toward investigating the effectiveness of a treatment via a randomized trial is to split the population into control and treatment groups then compare the average response of the treatment group receiving the treatment to the control g...

Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks.

IEEE transactions on biomedical circuits and systems
The study of neuron interactions and hardware implementations are crucial research directions in neuroscience, particularly in developing large-scale biological neural networks. The FitzHugh-Nagumo (FHN) model is a popular neuron model with highly bi...

Innovative Metaheuristic Optimization Approach with a Bi-Triad for Rehabilitation Exoskeletons.

Sensors (Basel, Switzerland)
The present work proposes a comprehensive metaheuristic methodology for the development of a medical robot for the upper limb rehabilitation, which includes the topological optimization of the device, kinematic models (5 DOF), human-robot interface, ...

Operating under the influence: the effect of alcohol on operative performance using a virtual robotic training platform-an experimental comparative cohort study.

Journal of robotic surgery
An elevated percentage of medical personnel reports using alcohol to relieve stress. Levels of alcohol addiction are almost double that of the general population. Robotic surgery is becoming more widespread. The purpose of this study is to evaluate t...

Observer-based resilient dissipativity control for discrete-time memristor-based neural networks with unbounded or bounded time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This work focuses on the issue of observer-based resilient dissipativity control of discrete-time memristor-based neural networks (DTMBNNs) with unbounded or bounded time-varying delays. Firstly, the Luenberger observer is designed, and additionally ...

Design and implementation of origami robot ROS-based SLAM and autonomous navigation.

PloS one
In this study an innovative parameterized water-bomb wheel modeling method based on recursive solving are introduced, significantly reducing the modeling workload compared to traditional methods. A multi-link supporting structure is designed upon the...

Elevator block brake structural optimization design based on an approximate model.

PloS one
An Aquila optimizer-back propagation (AO-BP) neural network was used to establish an approximate model of the relationship between the design variables and the optimization objective to improve elevator block brake capabilities and achieve a lightwei...

Neural Q-learning for discrete-time nonlinear zero-sum games with adjustable convergence rate.

Neural networks : the official journal of the International Neural Network Society
In this paper, an adjustable Q-learning scheme is developed to solve the discrete-time nonlinear zero-sum game problem, which can accelerate the convergence rate of the iterative Q-function sequence. First, the monotonicity and convergence of the ite...

Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition.

Journal of applied toxicology : JAT
Cytochrome P450 (CYP) enzymes are involved in the metabolism of approximately 75% of marketed drugs. Inhibition of the major drug-metabolizing P450s could alter drug metabolism and lead to undesirable drug-drug interactions. Therefore, it is of great...