In order to identify multi micro objects, an improved support vector machine algorithm is present, which employs invariant moments based edge extraction to obtain feature attribute and then presents a heuristic attrib...
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Spiking neural P systems are a new computing model inspired from the biological phenomena that in the brain the neurons cooperate to deal with spikes by axons. Since it has been shown that they have powerful computati...
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Spiking neural P systems are a new computing model inspired from the biological phenomena that in the brain the neurons cooperate to deal with spikes by axons. Since it has been shown that they have powerful computational capability and potential capability in solving computationally hard problems, more and more people begin to get interested in this field. This paper firstly introduces the formal definition of standard spiking neural P systems and some notions which are often used in this area;then, several extensions of the original spiking neural P systems are summarized, that are: Extented SN P system;SN P system with exhaustive use of rules;Asynchronous SN P system;Sequential SN P system. Also, the results on the topic of spiking neural P systems are briefly recalled in two aspects: computational completeness and computational efficiency. In the end, two more important future research directions on spiking neural P systems are pointed out. Specifically, one interesting topic is to develop a new computing model which is more "realistic";another topic is to consider how to use these models in biological modeling and simulation.
In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algor...
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In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.
It is difficult to guide the entry vehicle to prescribed area due to the disperse of environment and kinematics. Through predicted residual range at the current state based on drag acceleration, we developed a predict...
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This paper presents an active disturbance rejection guidance method using quadratic transition for the atmospheric ascent guidance problem. The quadratic transition is designed from the current flight states with a re...
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作者:
Qiming LiuXinru CuiZhe LiuHesheng WangDepartment of Automation
Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence
AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation
Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China
Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-b...
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Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.
This study investigates the emergency decision-making problem in a multi-agent system. Departments are modeled as agents to perform coordinated planning to obtain a global action plan with a short execution time const...
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Smart health and emotional care powered by the Internet of Medical Things (IoMT) are revolutionizing the healthcare industry by adopting several technologies related to multimodal physiological data collection, commun...
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To facilitate the integration of learning resources categorized under different ontology representations, the techniques of ontology mapping can be applied. Though many algorithms and systems have been proposed for on...
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To facilitate the integration of learning resources categorized under different ontology representations, the techniques of ontology mapping can be applied. Though many algorithms and systems have been proposed for ontology mapping, they do not have an automatic weighting strategy on class features to automate the ontology mapping process. A novel method of computing the feature weights is proposed. By feature semantic analysis, the different entities similarity calculation model and weight calculation model were defined. The results show that it makes the ontology mapping process more automatic while retaining satisfying accuracy. Improve ontology mapping effectiveness.
A method based on multi-agents and ANN (Artificial Neural Network) was proposed to solve the pursuit-evasion task in continuous time-varying environment. According to this method, several autonomous agents with 8 circ...
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