AIMC Topic: Stochastic Processes

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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...
Young Adult Adult Sensitivity and Specificity Temperature Reproducibility of Results Support Vector Machine Monitoring, Physiologic Models, Statistical Male Adolescent Humans Algorithms Female Artificial Intelligence Infrared Rays Thermography Normal Distribution Respiratory Rate Stochastic Processes Body Temperature Respiration Signal-To-Noise Ratio Equipment Design Signal Processing, Computer-Assisted
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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...
Machine Learning Algorithms DNA Humans Neural Networks, Computer Signal Processing, Computer-Assisted Stochastic Processes Computers, Molecular Electroencephalography Seizures
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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...
Stochastic Processes Neural Networks, Computer Diffusion Markov Chains Humans
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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...
Time Factors Nonlinear Dynamics Neural Networks, Computer Stochastic Processes
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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...
Computer Simulation Models, Neurological Stochastic Processes Machine Learning Action Potentials Humans Software Algorithms
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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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Current Projection Methods-Induced Biases at Subgroup Detection for Machine-Learning Based Data-Analysis of Biomedical Data.

International journal of molecular sciences Dec 20, 2019
Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and, finally, the identification of relevant subgroups. Correct ...
Datasets as Topic Stochastic Processes Computational Biology Antigens, CD Flow Cytometry Machine Learning Algorithms Humans
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Finite-time and fixed-time anti-synchronization of Markovian neural networks with stochastic disturbances via switching control.

Neural networks : the official journal of the International Neural Network Society Nov 28, 2019
This paper proposes a unified theoretical framework to study the problem of finite/fixed-time drive-response anti-synchronization for a class of Markovian stochastic neural networks. State feedback switching controllers without the sign function are ...
Reaction Time Neural Networks, Computer Markov Chains Algorithms Feedback Stochastic Processes Time Factors
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Mean-field models in swarm robotics: a survey.

Bioinspiration & biomimetics Nov 6, 2019
We present a survey on the application of fluid approximations, in the form of mean-field models, to the design of control strategies in swarm robotics. Mean-field models that consist of ordinary differential equations, partial differential equations...
Robotics Feedback Models, Theoretical Stochastic Processes
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Massive computational acceleration by using neural networks to emulate mechanism-based biological models.

Nature communications Sep 25, 2019
For many biological applications, exploration of the massive parametric space of a mechanism-based model can impose a prohibitive computational demand. To overcome this limitation, we present a framework to improve computational efficiency by orders ...
Computer Simulation Models, Biological Neural Networks, Computer Escherichia coli Stochastic Processes Kinetics Entropy Algorithms
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