In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other *** existing track segment association algorithms have low correlation accuracy in dense distributed...
In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other *** existing track segment association algorithms have low correlation accuracy in dense distributed or long-time interruption situations. To this purpose, a dense multi-target track segment association(DMTTSA) algorithm is proposed. Firstly, two identical networks based on the multi-head probability sparse(ProbSparse) self-attention are used to capture the long-term dependencies of the tracks. Then, the bidirectional quadruplet hard sample loss(BiQuaHard loss) is constructed to make the tracks belonging to the same targets closer and the tracks belonging to the different targets farther. Finally, DMTTSA takes the closest track pairs in the feature space as the associated tracks and divides the unassociated tracks into the birth and dead tracks in chronological order. Some comparative experiments are carried out to show the anti-noise performance of the DMTTSA, as well as the effectiveness of solving the problem of dense multi-target track interruption.
Surface electromyographic(sEMG) signals play an important role in human-computer interaction between patients and rehabilitation robots in rehabilitation *** paper shows the effectiveness of one-dimensional convolutio...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Surface electromyographic(sEMG) signals play an important role in human-computer interaction between patients and rehabilitation robots in rehabilitation *** paper shows the effectiveness of one-dimensional convolutional neural networks(1-D CNN) in estimating hand motion intentions from sEMG *** database 1 was employed to train the ***,the data from a single subject was used to train a model,and the accuracy was roughly maintained at 80%.Then,the whole dataset was used to train the network,and the recognition accuracy was improved to 84.16%.This shows that 1-D CNN effectively estimates hand movements and achieves high accuracy even for a small number of data.
In this paper,a fractional-order cyclic gene regulatory network model with time delay is ***,the total time delay of the system is selected as the bifurcation parameter,and the condition for the existence of Hopf bifu...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,a fractional-order cyclic gene regulatory network model with time delay is ***,the total time delay of the system is selected as the bifurcation parameter,and the condition for the existence of Hopf bifurcation is derived by analyzing its characteristic *** is found that the time delay affects the stability of the system,and the order affects the position of the bifurcation *** the time delay is greater than the critical time delay,the system loses ***,a state feedback controller is designed for the unstable *** is proved that the control method has good control effect for the system instability caused by Hopf ***,the correctness of the theoretical derivation is verified by simulation.
Soft sensing mainly studies the real-time prediction of some key performance indicators or quality variables in the actual production process,which has the role of guiding production in the actual production *** stack...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Soft sensing mainly studies the real-time prediction of some key performance indicators or quality variables in the actual production process,which has the role of guiding production in the actual production *** stacked autoencoder is a multi-layer autoencoder *** input variables will be encoded and decoded through each layer of autoencoders,and the obtained hidden features will be retained as the input of the next *** this way,high-level data features can be successfully learned from the input layer to the intermediate *** isomorphic autoencoder reconstruct an identical data input layer,and the reconstruction is performed by minimizing the error of the decoded data from the original input ***,for a soft measurement model,some data information may also reduce the accuracy or generalization of the *** order to overcome the above shortcomings,this paper proposes a gated stacked isomorphic autoencoder,which evaluates the contribution of each hidden layer feature through the gating unit,and then integrates the information of different hidden layers to complete the prediction and estimation of related main ***,the effectiveness and feasibility of the method are verified in practical industrial cases.
With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary ...
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This paper focuses on the coordinated tracking control scheme of dual-manipulator based on friction compensation. First, a new dual-manipulator model with flexible joints and friction is constructed;Second, a new adap...
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Blast furnace operating parameters regulate the gas utilization rate (GUR), and different operating parameters affect the GUR on different time scales. However, the existing methods only analyze and model the predicti...
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Power line network is the main carrier of the power system, and the smooth patrol inspection plays a crucial role in the fault prevention of the power line network. With the emergence of the patrol inspection UAV, how...
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This article studies the time-varying formation (TVF) problem of multiagent systems (MASs) with different time delays. By designing the control protocol, the followers could achieve the desired TVF. Considering differ...
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Although skeleton-based gesture recognition based on supervised learning has made promising achievements, the reliance on large amounts of annotation for training poses a significant cost. This paper addresses semi-su...
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