AIMC Topic: Markov Chains
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Fuzzy Stochastic Optimal Guaranteed Cost Control of Bio-Economic Singular Markovian Jump Systems.
IEEE transactions on cybernetics
Jan 15, 2015
This paper establishes a bio-economic singular Markovian jump model by considering the price of the commodity as a Markov chain. The controller is designed for this system such that its biomass achieves the specified range with the least cost in a fi...
Energy-to-peak state estimation for Markov jump RNNs with time-varying delays via nonsynchronous filter with nonstationary mode transitions.
IEEE transactions on neural networks and learning systems
Jan 6, 2015
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of n...
Energy Efficient Execution of POMDP Policies.
IEEE transactions on cybernetics
Dec 18, 2014
Recent advances in planning techniques for partially observable Markov decision processes (POMDPs) have focused on online search techniques and offline point-based value iteration. While these techniques allow practitioners to obtain policies for fai...
Mode-dependent stochastic stability criteria of fuzzy Markovian jumping neural networks with mixed delays.
ISA transactions
Dec 12, 2014
This paper investigates the stochastic stability of fuzzy Markovian jumping neural networks with mixed delays in mean square. The mixed delays include time-varying delay and continuously distributed delay. By using the Lyapunov functional method, Jen...
Global exponential stability of delayed Markovian jump fuzzy cellular neural networks with generally incomplete transition probability.
Neural networks : the official journal of the International Neural Network Society
Nov 4, 2014
The problem of global exponential stability in mean square of delayed Markovian jump fuzzy cellular neural networks (DMJFCNNs) with generally uncertain transition rates (GUTRs) is investigated in this paper. In this GUTR neural network model, each tr...
Learning to track multiple targets.
IEEE transactions on neural networks and learning systems
Jul 14, 2014
Monocular multiple-object tracking is a fundamental yet under-addressed computer vision problem. In this paper, we propose a novel learning framework for tracking multiple objects by detection. First, instead of heuristically defining a tracking algo...
Stochastic abstract policies: generalizing knowledge to improve reinforcement learning.
IEEE transactions on cybernetics
May 13, 2014
Reinforcement learning (RL) enables an agent to learn behavior by acquiring experience through trial-and-error interactions with a dynamic environment. However, knowledge is usually built from scratch and learning to behave may take a long time. Here...
Cost-effectiveness of opportunistic osteoporosis screening using chest radiographs with deep learning in Germany.
Aging clinical and experimental research
May 13, 2025
BACKGROUND: Osteoporosis is often underdiagnosed due to limitations in traditional screening methods, leading to missed early intervention opportunities. AI-driven screening using chest radiographs could improve early detection, reduce fracture risk,...
Hidden Markov model-based similarity measure (HMM-SM) for gait quality assessment of lower-limb prosthetic users using inertial sensor signals.
Journal of neuroengineering and rehabilitation
May 12, 2025
BACKGROUND: Gait quality indices, such as the Gillette Gait Index or Gait Profile Score (GPS), can provide clinicians with objective, straightforward measures to quantify gait pathology and monitor changes over time. However, these methods often requ...
Individualized multi-treatment response curves estimation using RBF-net with shared neurons.
Biometrics
Jan 7, 2025
Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific interests lie in identifying the differential effect of different treatments based on some external covariates. We propose a novel non-parametric treatm...
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