AIMC Topic: Markov Chains

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Target Tracking Control of a Biomimetic Underwater Vehicle Through Deep Reinforcement Learning.

IEEE transactions on neural networks and learning systems Aug 3, 2022
In this article, the underwater target tracking control problem of a biomimetic underwater vehicle (BUV) is addressed. Since it is difficult to build an effective mathematic model of a BUV due to the uncertainty of hydrodynamics, target tracking cont...
Neural Networks, Computer Algorithms Biomimetics Markov Chains Reinforcement, Psychology
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Sampled-Data Synchronization of Stochastic Markovian Jump Neural Networks With Time-Varying Delay.

IEEE transactions on neural networks and learning systems Aug 3, 2022
In this article, sampled-data synchronization problem for stochastic Markovian jump neural networks (SMJNNs) with time-varying delay under aperiodic sampled-data control is considered. By constructing mode-dependent one-sided loop-based Lyapunov func...
Neural Networks, Computer Algorithms Computer Simulation Markov Chains Stochastic Processes
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Frame-Correlation Transfers Trigger Economical Attacks on Deep Reinforcement Learning Policies.

IEEE transactions on cybernetics Jul 19, 2022
Adversarial attack can be deemed as a necessary prerequisite evaluation procedure before the deployment of any reinforcement learning (RL) policy. Most existing approaches for generating adversarial attacks are gradient based and are extensive, viz.,...
Machine Learning Learning Policy Markov Chains Reinforcement, Psychology
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Resilient Asynchronous State Estimation for Markovian Jump Neural Networks Subject to Stochastic Nonlinearities and Sensor Saturations.

IEEE transactions on cybernetics Jul 4, 2022
This article studies the problem of dissipativity-based asynchronous state estimation for a class of discrete-time Markov jump neural networks subject to randomly occurring nonlinearities, sensor saturations, and stochastic parameter uncertainties. F...
Neural Networks, Computer Computer Simulation Communication Time Factors Markov Chains
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Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure.

ESC heart failure Jun 23, 2022
AIMS: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF).
Humans Artificial Intelligence Hospitalization Risk Assessment Chronic Disease Heart Failure Markov Chains
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General Decay Stability for Nonautonomous Neutral Stochastic Systems With Time-Varying Delays and Markovian Switching.

IEEE transactions on cybernetics Jun 16, 2022
A new type of asymptotic stability for nonlinear hybrid neutral stochastic systems with constant delays was investigated recently, where the criteria depended on the delays' sizes. Unfortunately, developed theory so far is not sufficient to deal with...
Neural Networks, Computer Algorithms Computer Simulation Markov Chains Stochastic Processes
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Finite-frequency control for nonlinear semi-Markov jump systems with piecewise transition probabilities.

ISA transactions Jun 2, 2022
Considering the frequency effect of external disturbances, this paper concerns the finite-frequency control problem for nonlinear semi-Markov jump systems (SMJSs) with piecewise transition probabilities (TPs) via the Takagi-Sugeno (T-S) fuzzy modelin...
Algorithms Computer Simulation Fuzzy Logic Markov Chains
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A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods.

IEEE transactions on medical imaging May 2, 2022
The ideal observer (IO) sets an upper performance limit among all observers and has been advocated for assessing and optimizing imaging systems. For general joint detection and estimation (detection-estimation) tasks, estimation ROC (EROC) analysis h...
Computer Simulation ROC Curve Bayes Theorem Supervised Machine Learning Markov Chains Monte Carlo Method
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Deep Reinforcement Learning With Modulated Hebbian Plus Q-Network Architecture.

IEEE transactions on neural networks and learning systems May 2, 2022
In this article, we consider a subclass of partially observable Markov decision process (POMDP) problems which we termed confounding POMDPs. In these types of POMDPs, temporal difference (TD)-based reinforcement learning (RL) algorithms struggle, as ...
Neural Networks, Computer Algorithms Reward Markov Chains Reinforcement, Psychology
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Asynchronous Distributed Finite-Time H Filtering in Sensor Networks With Hidden Markovian Switching and Two-Channel Stochastic Attack.

IEEE transactions on cybernetics Mar 11, 2022
This article investigates the asynchronous distributed finite-time H filtering problem for nonlinear Markov jump systems over sensor networks under stochastic attacks. The stochastic attacks, called two-channel deception attacks, exist not only betwe...
Neural Networks, Computer Markov Chains
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