Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered o...
Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered out. In the case of EEG signals, smoothing filters gave very good results. In this paper, various types of smoothing filters for the analysis of infrared spectroscopy signals were compared.
A 0-3 piezoelectric composite material composed of piezoelectric ceramic particles and polymers combines the performance advantages of both components and has broad prospects for applications in piezoelectric pressure...
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False data injection attack(FDIA) is a traditional attack for the smart grid. There are many methods for the detection of the FDIA, but few of them can send the attack alarm successfully without an attack model. In th...
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ISBN:
(纸本)9781665402460
False data injection attack(FDIA) is a traditional attack for the smart grid. There are many methods for the detection of the FDIA, but few of them can send the attack alarm successfully without an attack model. In this paper, we propose a reinforcement learning-based FDIA detection method for the distributed smart grid. The detection problem is formulated as a partially observable Markov decision process(POMDP) problem, and the observation of the POMDP can be obtained from the estimation of state and attack which come from the Kalman filter. By using the Sarsa algorithm, we can get a Q-table through online training. Finally, we use the IEEE-118 bus power system to evaluate the performance of our detector, and numerical results show the accurate response for the FDIA.
In the industrial field, compound faults often occur on rolling bearings and it's difficult to diagnose them correctly. To solve this problem, this article proposes a CNN-ELM compound fault diagnosis method based ...
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This paper investigates a pattern formation control problem for a multi-agent system modeled with given interaction topology, in which m of the n agents are chosen as leaders and consequently a control signal is added...
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2D/3D medical image registration of pre-operative volumes and intra-operative images plays an important role in neurological interventions. However, vast space of transformation parameters makes this task incredibly c...
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Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-...
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The proliferation of Internet-connected mobile devices has been a driving force in the evolution of mobile computing. Battery life and computational limitations inherent to these devices have steered mobile applicatio...
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Safe and effective path planning of multiple combat vehicles engaged in antagonistic environments keeps a challenging problem. Based on the application background of multi-robots in cooperative reconnaissance of enemy...
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ISBN:
(纸本)9781665426480
Safe and effective path planning of multiple combat vehicles engaged in antagonistic environments keeps a challenging problem. Based on the application background of multi-robots in cooperative reconnaissance of enemy camps in environment with traps, this paper studies the multi-agent path planning based on bionic algorithms and artificial potential field method. The proposed bionic PP-AP Sarsa Scheme is inspired by food-finding scheme of Physarum Polycephalum (PP), which can effectively solve the dimensional explosion problem of traditional multi-agent reinforcement learning methods. This paper first studies the single-agent bionic planning problem with the PP algorithm to initialize the Q table used in Sarsa-based reinforcement learning, which effectively reduces the search space and accelerates the convergence speed of the early stage of reinforcement learning. After the Q tables in the same map are obtained through the training of different single agents, the Q tables of every agents are extended to multi-agents scenario by the assistance of simplified artificial potential field, hence a composite parallel path planner named RL-APCP 3 is constructed to synchronously update the actions of all of the agents, which allows us to complete the coordinated and efficient search of enemy camps by multiple agents. Compared with the Sarsa path planning algorithm of single agent, the efficiency of this scheme is improved up to 55.22%.
Active techniques have been introduced to give better detectability performance for cyber-attack diagnosis in cyber-physical systems (CPS). In this paper, switching multiplicative watermarking is considered, whereby w...
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