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Computer Simulation

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An adaptive variable-parameter dynamic learning network for solving constrained time-varying QP problem.

Neural networks : the official journal of the International Neural Network Society
To efficiently solve the time-varying convex quadratic programming (TVCQP) problem under equational constraint, an adaptive variable-parameter dynamic learning network (AVDLN) is proposed and analyzed. Being different from existing varying-parameter ...

Accelerating virtual patient generation with a Bayesian optimization and machine learning surrogate model.

CPT: pharmacometrics & systems pharmacology
The pharmaceutical industry has increasingly adopted model-informed drug discovery and development (MID3) to enhance productivity in drug discovery and development. Quantitative systems pharmacology (QSP), which integrates drug action mechanisms and ...

DFA-mode-dependent stability of impulsive switched memristive neural networks under channel-covert aperiodic asynchronous attacks.

Neural networks : the official journal of the International Neural Network Society
This article is concerned with the deterministic finite automaton-mode-dependent (DFAMD) exponential stability problem of impulsive switched memristive neural networks (SMNNs) with aperiodic asynchronous attacks and the network covert channel. First,...

Volume-preserving geometric shape optimization of the Dirichlet energy using variational neural networks.

Neural networks : the official journal of the International Neural Network Society
In this work, we explore the numerical solution of geometric shape optimization problems using neural network-based approaches. This involves minimizing a numerical criterion that includes solving a partial differential equation with respect to a dom...

Delayed-feedback oscillators replicate the dynamics of multiplex networks: Wavefront propagation and stochastic resonance.

Neural networks : the official journal of the International Neural Network Society
The widespread development and use of neural networks have significantly enriched a wide range of computer algorithms and promise higher speed at lower cost. However, the imitation of neural networks by means of modern computing substrates is highly ...

Barrier function-based prescribed performance trajectory tracking control of wheelchair upper-limb exoskeleton robot under actuator fault and external disturbance: Experimental verification.

ISA transactions
This paper presents an innovative control strategy for the trajectory tracking of wheelchair upper-limb exoskeleton robots, integrating sliding mode control with a barrier function-based prescribed performance approach to handle actuator faults and e...

Denoising low-field MR images with a deep learning algorithm based on simulated data from easily accessible open-source software.

Journal of magnetic resonance (San Diego, Calif. : 1997)
In this study, we introduce a denoising method aimed at improving the contrast ratio in low-field MRI (LFMRI) using an advanced 3D deep convolutional residual network model. Our approach employs synthetic brain imaging datasets that closely mimic the...

Robust parameter estimation and identifiability analysis with hybrid neural ordinary differential equations in computational biology.

NPJ systems biology and applications
Parameter estimation is one of the central challenges in computational biology. In this paper, we present an approach to estimate model parameters and assess their identifiability in cases where only partial knowledge of the system structure is avail...

Analysis and actuation design of a novel at-scale 3-DOF biomimetic flapping-wing mechanism inspired by flying insects.

Bioinspiration & biomimetics
Insects' flight is imbued with endless mysteries, offering valuable inspiration to the flapping-wing robots. Particularly, the multi-mode wingbeat motion such as flapping, sweeping and twisting in coordination presents advantages in promoting unstead...

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...