Noise suppression and resolution improvement are important issues in high-echo target ultrasound imaging detection. To address this problem, this paper proposes a phased array focused ultrasound imaging method based o...
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An optical-chaos secure communication of 86-Gb/s 16-ary QAM signal over 100-km fiber transmission is experimentally demonstrated under the 20%-overhead SD-FEC BER threshold of 2.0×10-2 by using wideband chaos syn...
ISBN:
(数字)9781839539268
An optical-chaos secure communication of 86-Gb/s 16-ary QAM signal over 100-km fiber transmission is experimentally demonstrated under the 20%-overhead SD-FEC BER threshold of 2.0×10-2 by using wideband chaos synchronization of discrete-mode semiconductor lasers.
Gaussian process (GP) regression is a popular statistical kernel method for learning the relationship hidden in data. However, the extensive calculation of kernel matrix hinders the further applications in many comput...
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Gaussian process (GP) regression is a popular statistical kernel method for learning the relationship hidden in data. However, the extensive calculation of kernel matrix hinders the further applications in many computer vision tasks such as super-resolution (SR). While active-sampling using active learning can extract a small informative subset from a large training set to overcome the bottleneck of GP regression based SR, there is still room for improving the SR quality as well as efficiency. In this paper, we target a nearly real-time GP-based SR, termed as SpGPR, by integrating the active-sampling and traditional sparse GP. The proposed framework is based on the statistics that the model projection vector is approximately sparse. To be more specific, we first train a full GP model based on an informative subset obtained by active sampling from the original training dataset. And then we propose to employ the sparse GP to further approximate the full GP model by seeking a sparse projection vector, which can significantly accelerate the prediction efficiency while getting higher reconstruction quality. The proposed method is fundamentally coarse-to-fine. Extensive experimental results indicate that the proposed method is superior to other state-of-art competitors and is promising for real-time SR application.
Data process of large rotating machinery is in line with basic features of information fusion. A framework of fault diagnosis and prediction based on sensor information fusion is built. An improved extracting method o...
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Data process of large rotating machinery is in line with basic features of information fusion. A framework of fault diagnosis and prediction based on sensor information fusion is built. An improved extracting method of features is used to deal with the information fusion of single sensor, which raises the calculation efficiency and precision. The local fault prediction process is presented, and the fault deterioration trend is judged on the basis of dynamic weighted method. Actual example of Beijing Yanshan Petrochemical Co. shows the correction of conclusion.
Some applications of the interconnected embedded systems such as sensor networks rely on all nodes in the network to execute certain tasks simultaneously. To meet this demand for simultaneity, a multi-timer model base...
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ISBN:
(纸本)9781509035502
Some applications of the interconnected embedded systems such as sensor networks rely on all nodes in the network to execute certain tasks simultaneously. To meet this demand for simultaneity, a multi-timer model based fully distributed task synchronization algorithm is proposed in this paper. In this multi-timer model, each node containing an embedded system is characterized by a timer. The microcontrollers (MCUs) within the interconnected embedded systems are switched to the assigned tasks by timer interrupts. Each timer decides when to trigger interrupts by only using the information from its neighbors. Task synchronization is realized by using the proposed synchronization algorithm. Some simulation examples are presented in the end to verify the effectiveness of the proposed synchronization algorithm.
Nonlocal interferometric phase filtering methods achieve excellent performance in both noise reduction and texture preservation, even in the case of complicated topography and low coherence. The main limitation of the...
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Nonlocal interferometric phase filtering methods achieve excellent performance in both noise reduction and texture preservation, even in the case of complicated topography and low coherence. The main limitation of the nonlocal methods is the computational burden. This paper proposed a nonlocal phase filtering strategy for the practical InSAR system, which combine the nonlocal algorithm with the traditional method to improve the efficiency.
Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using text descriptions or reference images, while preserving irrelevant attributes (e.g., identity, background, cloth). Many ...
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In this paper, continuous-time Zhang dynamics (CTZD) models and discrete-time Zhang dynamics (DTZD) models are proposed to solve in real time for the time-varying pth root, from real domain to complex domain. In addit...
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In this paper, continuous-time Zhang dynamics (CTZD) models and discrete-time Zhang dynamics (DTZD) models are proposed to solve in real time for the time-varying pth root, from real domain to complex domain. In addition, the convergence properties of the proposed Zhang dynamics (ZD) models are discussed and proved. Furthermore, exploiting different parameters in the proposed ZD models is investigated in order to achieve superior convergence and better accuracy. Computer-simulation and experiment results further substantiate the efficacy of the proposed ZD models. Moreover, the superiority of DTZD models is verified by comparing with Newton-Raphson iteration (NRI).
The Coronavirus disease 2019 (COVID-19) has rapidly spread all over the world since its first report in December 2019 and thoracic computed tomography (CT) has become one of the main tools for its diagnosis. In recent...
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In this paper, the Zhang-gradient (ZG) method, which is a combination of Zhang dynamics (ZD) and gradient dynamics (GD) methods, is proposed for solving the tracking control problem of the multiple-input multiple-outp...
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ISBN:
(纸本)9781467391054
In this paper, the Zhang-gradient (ZG) method, which is a combination of Zhang dynamics (ZD) and gradient dynamics (GD) methods, is proposed for solving the tracking control problem of the multiple-input multiple-output (MIMO) system. Different from the traditional ZG method, GD is used additionally twice more in this paper to get through the derivation procedure. Moreover, each GD parameter is tunable for each GD design formula instead of being traditionally assigned the same value, which is the key point in this research for making simulations successful. Besides, simulation verifications further illustrate that the proposed controller group based on the ZG method achieves not only satisfactory tracking accuracy but also rapid tracking rate.
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