It is difficult to train a trustworthy transformer model on a small image classification dataset. This research proposes a sophisticated structured knowledge distillation algorithm that uses CNNs as Transformer's ...
Aiming at the problem of low semantic segmentation accuracy of tiny targets in UAV aerial images, a bilateral semantic segmentation network T-BiseNetv2 is proposed. The proposed segmentation network is based on BiseNe...
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In this paper, the stability analysis of Load frequency Control (LFC) systems with time-varying delay is conducted. Firstly, an augmented Lyapunov-Krasovskii (L-K) functional is designed to incorporate the relevant in...
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Based on mode coupling theory and angular momentum matching principle, the generation process and mechanism of radial higher-order orbital angular momentum (OAM) based on helically-twisted elliptic fiber (HTEF) is ana...
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This study presents a new machine learning algorithm, named Chemical Environment Graph Neural Network (ChemGNN), designed to accelerate materials property prediction and advance new materials discovery. Graphitic carb...
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In this paper, a simplified self-coherent system achieved by Alamouti coding and digital subcarrier multiplexing technology is proposed. The transmission of 50Gbaud 4-subcarrier 16QAM signal over 40km single mode fibe...
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Tapped delay lines and recurrent connections are two different components that are used along to design a time-delay recurrent neural network with a stochastic gradient descent algorithm in combination with a dropout ...
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Reduced state DRE for clipping-And-quantization noise elimination is studied with 3-bit DAC. Experiment-results indicate that 99.2% computational complexity reduction can be achieved for 40Gbaud PAM-8 signal, maintain...
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The cloud boundary network environment is characterized by a passive defense strategy,discrete defense actions,and delayed defense feedback in the face of network attacks,ignoring the influence of the external environ...
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The cloud boundary network environment is characterized by a passive defense strategy,discrete defense actions,and delayed defense feedback in the face of network attacks,ignoring the influence of the external environment on defense decisions,thus resulting in poor defense ***,this paper proposes a cloud boundary network active defense model and decision method based on the reinforcement learning of intelligent agent,designs the network structure of the intelligent agent attack and defense game,and depicts the attack and defense game process of cloud boundary network;constructs the observation space and action space of reinforcement learning of intelligent agent in the non-complete information environment,and portrays the interaction process between intelligent agent and environment;establishes the reward mechanism based on the attack and defense gain,and encourage intelligent agents to learn more effective defense *** designed active defense decision intelligent agent based on deep reinforcement learning can solve the problems of border dynamics,interaction lag,and control dispersion in the defense decision process of cloud boundary networks,and improve the autonomy and continuity of defense decisions.
Neural network-assisted pre-distortion method is proposed to generate pattern errors with memory length of more than 5 symbols in PAM-8 IM/DD transmission utilizing limited samples as training sequence, which enables ...
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