We propose a method for reconstructing non-diffuse surfaces based on theπ-phase-shifted two-plus-one phase-shifting ***,we introduce a 2fH+a+2fM+2f_(L)method for unwrapped phase ***,we introduce a new set ofπ-phase-...
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We propose a method for reconstructing non-diffuse surfaces based on theπ-phase-shifted two-plus-one phase-shifting ***,we introduce a 2fH+a+2fM+2f_(L)method for unwrapped phase ***,we introduce a new set ofπ-phase-shifted 2fH+a/2+2fM+2f_(L)fringe patterns with halved background *** saturated pixels will be replaced with the unsaturated pixels in theπ-phase-shifted fringe ***,we analyze eight fringe replacement cases and give the corresponding phase calculation,and further give the general *** confirm that the sum of the phase error of the proposed method is 81.4%lower than that of the traditional method,and 61.5%lower than that of the adaptive fringe projection method.
Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic ***,it is still unclear how and why the EF-induced polarization ...
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Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic ***,it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic *** the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations,we suppose that the applied EFs could functionally modulate interneurons’response via regulating dendritic *** first,we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials,which characterizes the relationship among EF-induced spatial polarizations,dendritic integration,and somatic *** performing model-based singular perturbation analysis,it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output(sI/O)relationship of dendritic *** predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input,and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA ***,the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA ***,we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.
With the development of informationtechnology,radio communicationtechnology has made rapid *** radio signals that have appeared in space are difficult to classify without manually *** radio signal clustering methods...
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With the development of informationtechnology,radio communicationtechnology has made rapid *** radio signals that have appeared in space are difficult to classify without manually *** radio signal clustering methods have recently become an urgent need for this ***,the high complexity of deep learning makes it difficult to understand the decision results of the clustering models,making it essential to conduct interpretable *** paper proposed a combined loss function for unsupervised clustering based on *** combined loss function includes reconstruction loss and deep clustering *** clustering loss is added based on reconstruction loss,which makes similar deep features converge more in feature *** addition,a features visualization method for signal clustering was proposed to analyze the interpretability of autoencoder utilizing Saliency *** experiments have been conducted on a modulated signal dataset,and the results indicate the superior performance of our proposed method over other clustering *** particular,for the simulated dataset containing six modulation modes,when the SNR is 20dB,the clustering accuracy of the proposed method is greater than 78%.The interpretability analysis of the clustering model was performed to visualize the significant features of different modulated signals and verified the high separability of the features extracted by clustering model.
This paper explores using convolutional neural networks (CNNs) for unsupervised image segmentation. The method enhances pixel labeling accuracy through superpixel and propagates back strategies. Leveraging CNN’s feat...
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Adaptive dwell scheduling is essential to achieve full performance for a simultaneous multi-beam radar *** dwell scheduling for such a radar system considering desired execution time criterion is studied in this *** p...
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Adaptive dwell scheduling is essential to achieve full performance for a simultaneous multi-beam radar *** dwell scheduling for such a radar system considering desired execution time criterion is studied in this *** primary objective of this model is to achieve maximum scheduling gain and minimum scheduling cost while adhering to not only time,aperture,and frequency constraints,but also electromagnetic compatibility(EMC)*** dwell scheduling algorithm is proposed to solve the above optimization problem,where several separation points are set on the timeline,so that each separator divides the scheduling interval into two *** the two sides,the dual-side time pointers are introduced,which move from the separator to both ends of the scheduling *** dwell tasks are analyzed in sequence at each analysis point based on their two-level synthetical *** tasks are then executed simultaneously by sharing the whole aperture under various constraints to accomplish multiple tasks *** above process is respectively conducted at each separator,and the final scheduling result is the one with the minimal cost among *** results prove that the proposed algorithm can achieve real-time dwell scheduling and outperform the existing algorithms in terms of scheduling performance.
Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering ***, research on PHM framework development for radar systems i...
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Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering ***, research on PHM framework development for radar systems is limited. Furthermore, typical PHM approaches are centralized, do not scale well, and are challenging to *** paper proposes an integrated PHM framework for radar systems based on system structural decomposition to enhance reliability and support maintenance actions. The complexity challenge associated with implementing PHM at the system level is addressed by dividing the radar system into subsystems. Subsequently, optimal measurement point selection and sensor placement algorithms are formulated for effective data acquisition. Local modules are developed for each subsystem health assessment, fault diagnosis, and fault prediction without a centralized controller. Maintenance decisions are based on each local module’s fault diagnosis and prediction results. To further improve the effectiveness of the prognostics stage, the feasibility of integrating deep learning (DL) models is also *** experiments with different degradation patterns are performed to evaluate the effectiveness of the framework’s DLbased prognostics model. The proposed framework facilitates transitioning from traditional reactive maintenance practices to a predictive maintenance approach, thereby reducing downtime and improving the overall availability of radar systems.
By simultaneously exploiting platform motion information and the phase differences among different channels, multichannel synthetic aperture radar has the ability to realize forward-looking imaging. However, existing ...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.
Nyquist Folding Receiver(NYFR)is a perceptron structure that realizes a low probability of intercept(LPI)signal analog to *** at the problem of LPI radar signal receiving,the time domain,frequency domain,and time-freq...
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Nyquist Folding Receiver(NYFR)is a perceptron structure that realizes a low probability of intercept(LPI)signal analog to *** at the problem of LPI radar signal receiving,the time domain,frequency domain,and time-frequency domain problems of signals intercepted by NYFR structure are *** with the time-frequency analysis(TFA)method,a radar recognition scheme based on deep learning(DL)is introduced,which can reliably classify common LPI radar ***,the structure of NYFR and its characteristics in the time domain,frequency domain,and time and frequency domain are ***,the received signal is then converted into a time-frequency image(TFI).Finally,four kinds of DL algorithms are used to classify LPI radar *** results demonstrate the correctness of the NYFR structure,and the effectiveness of the proposed recognition method is verified by comparison experiments.
Time synchronization is one of the base techniques in wireless sensor networks(WSNs).This paper proposes a novel time synchronization protocol which is a robust consensusbased algorithm in the existence of transmissio...
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Time synchronization is one of the base techniques in wireless sensor networks(WSNs).This paper proposes a novel time synchronization protocol which is a robust consensusbased algorithm in the existence of transmission delay and packet *** compensates for transmission delay and packet loss firstly,and then,estimates clock skew and clock offset in two *** and experiment results show that the proposed protocol can keep synchronization error below 2μs in the grid network of 10 nodes or the random network of 90 ***,the synchronization accuracy in the proposed protocol can keep constant when the WSN works up to a month.
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