Siamese transformer network-based similarity metric learning for cross-source remote sensing image retrieval

Neural Computing and Applications - As a fundamental technique for mining and analysis of remote sensing (RS) big data, content-based remote sensing image retrieval (CBRSIR) has received a lot of...     

Semi-supervised transformable architecture search for feature distillation

Pattern Analysis and Applications - The designed method aims to perform image classification tasks efficiently and accurately. Different from the traditional CNN-based image classification methods,...     

A quantized set-membership estimation-based heading control method of unmanned surface vessels under unknown-but-bounded wave-induced disturbances

This paper is concerned with the heading tracking control problem for a network-based unmanned surface vessel (USV) under wave-induced disturbances. Considering the characteristics of the wave-induced disturbances, the unknown-but-bounded (UBB) noise model is adopted. Meanwhile, signal quantization is taken into account due to the limited capacity of the communication channel. Based on these considerations, a novel set-membership based control scheme is proposed, which consists of a set-membership filter (SMF) and a set-membership controller (SMC). In the proposed control scheme, the SMF is designed for providing an ellipsoidal estimation set for the USV at each sampling step, and then the SMC uses the estimation set for producing control input for the USV in order to track the reference. Sufficient conditions are derived for the considered USV system to be asymptotically stable and satisfy the modified set-membership performance constraint. Simulation results verifies the effectiveness of the proposed control scheme.     

Adaptive prescribed time control for quadrotor formation with stochastic links failure

The formation control for multiple quadrotors subject to maintaining the formation configuration and collision avoidance in the situation of stochastic links failure is investigated in this paper. First, the distributed formation controller is designed, the position controller is developed to manage the desired formation of position, and the attitude controller is developed to control the translation and rotation movements of the quadrotor. Then, in order to avoid the collisions between multiple quadrotors and the obstacles, a potential energy function method is introduced into the quadrotor formation control combined with the nest adaptive control. Inspired by the design of event trigger controller, a communication compensation controller is designed to ensure the stability of quadrotor formation under the condition of random communication interruption and recovery. Moreover, a prescribed time function is designed, which means the convergence time of the formation system can be set in advance. The prescribed time stability of the formation control system is proved by Lyapunov theory. Finally, the simulation results verify the effectiveness and superiority of this method.     

On measuring network robustness for weighted networks

Knowledge and Information Systems - Network robustness measures how well network structure is strong and healthy when it is under attack, such as vertices joining and leaving. It has been widely...     

Relational attention-based Markov logic network for visual navigation

The Journal of Supercomputing - We argue the agent’s low generalization problem for searching target object in challenging visual navigation could be solved by "how" and...     

Distributed algorithm for mixed equilibrium problems with event-triggered strategy

Neural Computing and Applications - A new iterative method based on the event-triggered strategy for finding a solution to a mixed equilibrium problem (MEP) is introduced in this paper. The target...     

Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network

Computational Economics - The study aims to analyze and forecast Internet financial risks based on the model based on deep learning and the Back Propagation Neural Network (BPNN). First, the theory...     

Bioinspired yeast microcapsules loaded with self-assembled nanotherapies for targeted treatment of cardiovascular disease

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