AIMC Topic: Stochastic Processes

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Viewpoint on Time Series and Interrupted Time Series Optimum Modeling for Predicting Arthritic Disease Outcomes.

Current rheumatology reports May 20, 2020
PURPOSE OF REVIEW: The propose of this viewpoint is to improve or facilitate the clinical decision-making in the management/treatment strategies of arthritis patients through knowing, understanding, and having access to an interactive process allowin...
Humans Arthritis Stochastic Processes Interrupted Time Series Analysis Machine Learning Linear Models Artificial Intelligence
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Physics-informed neural networks for solving nonlinear diffusivity and Biot's equations.

PloS one May 6, 2020
This paper presents the potential of applying physics-informed neural networks for solving nonlinear multiphysics problems, which are essential to many fields such as biomedical engineering, earthquake prediction, and underground energy harvesting. S...
Neural Networks, Computer Computer Simulation Nonlinear Dynamics Algorithms Stochastic Processes
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Deep learning for computational structural optimization.

ISA transactions Apr 10, 2020
We investigate a novel computational approach to computational structural optimization based on deep learning. After employing algorithms to solve the stiffness formulation of structures, we used their improvement to optimize the structural computati...
Algorithms Reproducibility of Results Least-Squares Analysis Image Interpretation, Computer-Assisted Deep Learning Stress, Mechanical Neural Networks, Computer Stochastic Processes
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Segmentation of prostate and prostate zones using deep learning : A multi-MRI vendor analysis.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] Mar 27, 2020
PURPOSE: Develop a deep-learning-based segmentation algorithm for prostate and its peripheral zone (PZ) that is reliable across multiple MRI vendors.
Male Deep Learning Imaging, Three-Dimensional Humans Algorithms Datasets as Topic Stochastic Processes Magnetic Resonance Imaging Prostate
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Human respiration monitoring using infrared thermography and artificial intelligence.

Biomedical physics & engineering express Mar 13, 2020
The respiration rate (RR) is the most vital parameter used for the determination of human health. The most widely adopted techniques, used to monitor the RR are contact in nature and face many drawbacks. This paper reports the use of Infrared Thermog...
Stochastic Processes Normal Distribution Respiratory Rate Infrared Rays Thermography Equipment Design Signal Processing, Computer-Assisted Respiration Signal-To-Noise Ratio Body Temperature Temperature Support Vector Machine Reproducibility of Results Monitoring, Physiologic Female Models, Statistical Male Adult Adolescent Sensitivity and Specificity Young Adult Humans Artificial Intelligence Algorithms
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Molecular and DNA Artificial Neural Networks via Fractional Coding.

IEEE transactions on biomedical circuits and systems Mar 9, 2020
This article considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using f...
Stochastic Processes Computers, Molecular Seizures Signal Processing, Computer-Assisted Neural Networks, Computer Machine Learning DNA Electroencephalography Algorithms Humans
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Resilient fault-tolerant anti-synchronization for stochastic delayed reaction-diffusion neural networks with semi-Markov jump parameters.

Neural networks : the official journal of the International Neural Network Society Feb 28, 2020
This paper deals with the anti-synchronization issue for stochastic delayed reaction-diffusion neural networks subject to semi-Markov jump parameters. A resilient fault-tolerant controller is utilized to ensure the anti-synchronization in the presenc...
Markov Chains Humans Neural Networks, Computer Stochastic Processes Diffusion
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Improved value iteration for neural-network-based stochastic optimal control design.

Neural networks : the official journal of the International Neural Network Society Jan 28, 2020
In this paper, a novel value iteration adaptive dynamic programming (ADP) algorithm is presented, which is called an improved value iteration ADP algorithm, to obtain the optimal policy for discrete stochastic processes. In the improved value iterati...
Neural Networks, Computer Time Factors Stochastic Processes Nonlinear Dynamics
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Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jan 20, 2020
Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory foot...
Algorithms Computer Simulation Models, Neurological Machine Learning Software Action Potentials Humans Stochastic Processes
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Cluster stochastic synchronization of complex dynamical networks via fixed-time control scheme.

Neural networks : the official journal of the International Neural Network Society Jan 7, 2020
By means of fixed-time (FDT) control technique, cluster stochastic synchronization of complex networks (CNs) is investigated. Quantized controller is designed to realize the synchronization of CNs within a settling time. FDT synchronization criteria ...
Neural Networks, Computer Stochastic Processes
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