AIMC Topic: Computer Simulation

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A Deep Learning-Based Generalized Empirical Flow Model of Glottal Flow During Normal Phonation.

Journal of biomechanical engineering
This paper proposes a deep learning-based generalized empirical flow model (EFM) that can provide a fast and accurate prediction of the glottal flow during normal phonation. The approach is based on the assumption that the vibration of the vocal fold...

Hierarchical multiloop MPC scheme for robot manipulators with nonlinear disturbance observer.

Mathematical biosciences and engineering : MBE
This paper addresses the robust enhancement problem in the control of robot manipulators. A new hierarchical multiloop model predictive control (MPC) scheme is proposed by combining an inverse dynamics-based feedback linearization and a nonlinear dis...

An improved ant colony algorithm for integrating global path planning and local obstacle avoidance for mobile robot in dynamic environment.

Mathematical biosciences and engineering : MBE
To improve the path optimization effect and search efficiency of ant colony optimization (ACO), an improved ant colony algorithm is proposed. A collar path is generated based on the known environmental information to avoid the blindness search at ear...

Uneven wrapped phase pattern denoising using a deep neural network.

Applied optics
The wrapped phase patterns obtained from an object composed of different materials have uneven gray values. In this paper, we improve the dilated-blocks-based deep convolution neural network (DBDNet) and build a new dataset for restoring the uneven g...

A survey of adaptive optimal control theory.

Mathematical biosciences and engineering : MBE
This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea ...

Scalability of Large Neural Network Simulations via Activity Tracking With Time Asynchrony and Procedural Connectivity.

Neural computation
We present a new algorithm to efficiently simulate random models of large neural networks satisfying the property of time asynchrony. The model parameters (average firing rate, number of neurons, synaptic connection probability, and postsynaptic dura...

Edge detection in single multimode fiber imaging based on deep learning.

Optics express
We propose a new edge detection scheme based on deep learning in single multimode fiber imaging. In this scheme, we creatively design a novel neural network, whose input is a one-dimensional light intensity sequence, and the output is the edge detect...

Dynamics study on the effect of memristive autapse distribution on Hopfield neural network.

Chaos (Woodbury, N.Y.)
As the shortest feedback loop of the nervous system, autapse plays an important role in the mode conversion of neurodynamics. In particular, memristive autapses can not only facilitate the adjustment of the dynamical behavior but also enhance the com...

[A protein complex recognition method based on spatial-temporal graph convolution neural network].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To propose a new method for mining complexes in dynamic protein network using spatiotemporal convolution neural network.

Best practice and reproducible science are required to advance artificial intelligence in real-world applications.

Briefings in bioinformatics
Drug-induced liver injury (DILI) is one of the most significant concerns in medical practice but yet it still cannot be fully recapitulated with existing in vivo, in vitro and in silico approaches. To address this challenge, Chen et al. [ 1] develope...