Finite Dimensional State Representation of Linear and Nonlinear Delay Systems
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Dynamics and Differential Equations"
DOI: 10.1007/s10884-017-9611-5
Abstract: We consider the question of when delay systems, which are intrinsically infinite dimensional, can be represented by finite dimensional systems. Specifically, we give conditions for when all the information about the solutions of the delay… read more here.
Keywords: state representation; finite dimensional; delay; delay systems ... See more keywords
State representation in mental illness
Sign Up to like & getrecommendations! Published in 2019 at "Current Opinion in Neurobiology"
DOI: 10.1016/j.conb.2019.03.011
Abstract: Reinforcement learning theory provides a powerful set of computational ideas for modeling human learning and decision making. Reinforcement learning algorithms rely on state representations that enable efficient behavior by focusing only on aspects relevant to… read more here.
Keywords: state; state representation; neurobiology; representation mental ... See more keywords
Online reinforcement learning of state representation in recurrent network supported by the power of random feedback and biological constraints
Sign Up to like & getrecommendations! Published in 2025 at "eLife"
DOI: 10.1101/2024.08.22.609100
Abstract: Representation of external and internal states in the brain plays a critical role in enabling suitable behavior. Recent studies suggest that state representation and state value can be simultaneously learnt through Temporal-Difference-Reinforcement-Learning (TDRL) and Backpropagation-Through-Time… read more here.
Keywords: representation; state representation; random feedback; reinforcement learning ... See more keywords
Observations Temporal Permutation-Based Self-Supervised Reinforcement Learning for UAV Active Object Detection
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2025.3621519
Abstract: In passive ground target detection using unmanned aerial vehicles (UAVs), some detrimental factors, like occlusion, significantly impact target detection performance. Active object detection (AOD) offers an effective way to address it, which usually uses deep… read more here.
Keywords: detection; active object; representation; state representation ... See more keywords
An Event-Driven Neural Kalman Model for State Representation and Learning-Based Dynamic Scheduling of Industrial Energy System
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2025.3593846
Abstract: Operation optimization of industrial energy systems (IES) can effectively improve energy utilization efficiency and reduce carbon emissions. Learning-based optimization models such as reinforcement learning (RL) have been widely applied in dynamic scheduling of energy systems.… read more here.
Keywords: neural kalman; energy; state representation; event driven ... See more keywords