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As an integral part of reliable communication in wireless networks, effective link estimation is essential for routing protocols. However, due to the dynamic nature of wireless channels, accurate link quality estimation remains a challenging task. In this paper, we propose 4C, a novel link estimator that applies link quality prediction along with link estimation. Our approach is data-driven and consists...
Objective: Investigate syndromes classification of fatty liver. Method: Investigate the relationship between syndrome differentiation and symptom of fatty liver by using SOM neural network and whole network analysis method, and provide references for the standardization of syndrome differentiation. Analysis on centrality was carried out to evaluate the importance of each symptom in each syndrome differentiation...
Terahertz(THz)radiation, which occupies a relatively unexplored portion of the electromagnetic spectrum between mid-infrared and microwave bands, offers innovative sensing and imaging technologies that can provide information unavailable through conventional methods such as microwave and X-ray techniques. Spectroscopy in the terahertz frequency range has demonstrated unique identification of both...
The paper provides a new idea on improving the calculating speed of the complex economic system evaluation by adopting the LM algorithms based on BP artificial neural network. It deeply discusses the concrete implementation process of LM and BP algorithms by using the comprehensive economic performance evaluation on fixed assets invest economic performance module as the example, and carries on the...
In this paper, we develop a fast and accurate synthesis way to effectively generate CMOS spiral inductor's layout parameter using artificial neural network methodology. Under our synthesis methodology, we can simulate and synthesis the geometric parameters of spiral inductor's layout up to the frequency of 20 GHz. Experiments and Results based on octagon differential spiral inductors of TSMC 0.13um...
A new neural network aided unscented Kalman filter is presented for tracking maneuvering target in distributed acoustic sensor networks. In practice, the system dynamics of these problems are usually incompletely observed, there may be large modeling errors when the target is maneuverable and some parameters of the system models may be inaccurate. So we propose using an offline trained neural network...
A novel comprehensive and automatic wide-band artificial neural network (ANN)-based modeling methodology for radio-frequency (RF) components is presented. The methodology is applied to differential spiral inductors with various geometrical sizes. The established model is tested with 653 inductors and shows excellent accuracy over the frequency range of 1-20 GHz
A new model for spiral inductors, which covers wide operation frequency range and full design parameters, is proposed by using artificial neural network (ANN). It is pointed out that a four-layered neural network is superior to a three-layered neural network both on the mapping and generalization abilities in spiral inductor modeling. For the first time, a novel physics-based sampling technique is...
In order to identify the rotating machinery fault, a method based on support vector machine (SVM) is proposed in this paper. After the feature vectors from the fault signals by means of wavelet packet are extracted and the support vector machine (SVM) classification algorithm to the classification of faults in rolling bearing is applied. By drawing a comparison between the classification and BP neural...
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