AIMC Topic: Stochastic Processes

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The Synchronization Analysis of Cohen-Grossberg Stochastic Neural Networks with Inertial Terms.

Computational intelligence and neuroscience May 25, 2022
The exponential synchronization (ES) of Cohen-Grossberg stochastic neural networks with inertial terms (CGSNNIs) is studied in this paper. It is investigated in two ways. The first way is using variable substitution to transform the system to another...
Time Factors Stochastic Processes Neural Networks, Computer Algorithms Computer Simulation
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Practical Exponential Stability of Impulsive Stochastic Reaction-Diffusion Systems With Delays.

IEEE transactions on cybernetics May 19, 2022
This article studies the practical exponential stability of impulsive stochastic reaction-diffusion systems (ISRDSs) with delays. First, a direct approach and the Lyapunov method are developed to investigate the p th moment practical exponential stab...
Time Factors Diffusion Stochastic Processes Neural Networks, Computer Algorithms
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A framework for preparing a stochastic nonlinear integrate-and-fire model for integrated information theory.

Network (Bristol, England) Apr 5, 2022
This paper presents a framework for spiking neural networks to be prepared for the Integrated Information Theory (IIT) analysis, using a stochastic nonlinear integrate-and-fire model. The model includes the crucial dynamics of the all-or-none law and...
Information Theory Action Potentials Neurons Stochastic Processes Neural Networks, Computer Computer Simulation Reproducibility of Results Models, Neurological
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A machine learning approach to identify stochastic resonance in human perceptual thresholds.

Journal of neuroscience methods Mar 12, 2022
BACKGROUND: Stochastic resonance (SR) is achieved when a faint signal is improved with the addition of the appropriate amount of white noise. Perceptual thresholds are expected to follow a characteristic performance improvement curve as a function of...
Humans Machine Learning Stochastic Processes
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A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Scientific reports Dec 20, 2021
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe...
Scattering, Radiation Normal Distribution Electromagnetic Fields Head Microwaves Stochastic Processes Hemorrhagic Stroke Computer Simulation Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning ROC Curve Area Under Curve Neural Networks, Computer Algorithms Brain Humans
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DeepCME: A deep learning framework for computing solution statistics of the chemical master equation.

PLoS computational biology Dec 8, 2021
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogor...
Computational Biology Models, Chemical Probability Computer Simulation Deep Learning Statistics as Topic Stochastic Processes
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Aedes-AI: Neural network models of mosquito abundance.

PLoS computational biology Nov 19, 2021
We present artificial neural networks as a feasible replacement for a mechanistic model of mosquito abundance. We develop a feed-forward neural network, a long short-term memory recurrent neural network, and a gated recurrent unit network. We evaluat...
Neural Networks, Computer Databases, Factual Animals Systems Analysis Spatio-Temporal Analysis Vector Borne Diseases Computational Biology Humans Aedes United States Mosquito Vectors Population Dynamics Stochastic Processes Models, Biological Weather
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Correspondence between neuroevolution and gradient descent.

Nature communications Nov 2, 2021
We show analytically that training a neural network by conditioned stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise. ...
Stochastic Processes Neural Networks, Computer Algorithms Computer Simulation Mutation
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Efficient Prediction of Missed Clinical Appointment Using Machine Learning.

Computational and mathematical methods in medicine Oct 22, 2021
Public health and its related facilities are crucial for thriving cities and societies. The optimum utilization of health resources saves money and time, but above all, it saves precious lives. It has become even more evident in the present as the pa...
No-Show Patients Stochastic Processes Bayes Theorem Appointments and Schedules Computational Biology Decision Trees Humans Machine Learning Logistic Models Area Under Curve Neural Networks, Computer Algorithms Support Vector Machine Data Interpretation, Statistical Databases, Factual
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Competency of Neural Networks for the Numerical Treatment of Nonlinear Host-Vector-Predator Model.

Computational and mathematical methods in medicine Oct 4, 2021
The aim of this work is to introduce a stochastic solver based on the Levenberg-Marquardt backpropagation neural networks (LMBNNs) for the nonlinear host-vector-predator model. The nonlinear host-vector-predator model is dependent upon five classes, ...
Disease Vectors Vector Borne Diseases Stochastic Processes Predatory Behavior Neural Networks, Computer Models, Biological Nonlinear Dynamics Plant Diseases Computer Simulation Animals Computational Biology
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