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Deep residual network enhanced with multilevel residual-of-residual for automatic classification of radio signals for 5G and beyond systems. [PDF]
Sci RepJabeur R, Alaerjan A, Chikha HB.
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Improved Tercom Based on Fading Factor
Applied Mechanics and Materials, 2011In order to solve the problem of the traditional Tercom, which is sensitive to the speed error and yaw angle error, an improved Tercom approach using with fading factor is introduced. The basic idea of this approach is to estimate the navigation position by a novel correlation function.
Shou Lei Lu, Long Zhao, Chang Yun Zhang
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Sage Husa Adaptive Integrated Navigation Algorithm Based on Variable Fading Factor
2020 International Conference on Computer Network, Electronic and Automation (ICCNEA), 2020In order to solve the problem of selecting attenuation factor due to the contradiction between noise tracking accuracy and tracking sensitivity in traditional sage Husa adaptive filtering algorithm, a novel SAGE Husa adaptive integrated navigation algorithm based on sliding attenuation factor is proposed, which can detect the actual changes of noise ...
Xiuliang Huang +2 more
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Mining frequent pattern based on fading factor in data streams
2009 International Conference on Machine Learning and Cybernetics, 2009In order to improve the mining efficiency of frequent patterns in data streams, we present an algorithm DS-FPM for mining frequent patterns in data streams. First, a data structure DSFP-tree is constructed and the data stream is divided into a set of segments, then potential frequent itemsets on each segment are obtained by IGFA algorithm, while the ...
Jia-Dong Ren +4 more
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Multiple fading factors-based strong tracking variational Bayesian adaptive Kalman filter
Measurement, 2021Abstract If the system model or the statistical characteristics of noise are inaccurate, the past measurements will directly affect the accuracy of current state estimation or even lead to filtering divergence. To overcome above difficulties, a multiple fading factors-based strong tracking variational Bayesian adaptive Kalman filter is proposed ...
Cheng Pan +4 more
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Frequent Items Mining on Data Stream Based on Time Fading Factor
2009 International Conference on Artificial Intelligence and Computational Intelligence, 2009Most of the existing algorithms for mining frequent items on data stream do not emphasis the importance of the recent data items. We present an algorithm using a fading factor to detect the data items with frequency counts exceeding a user-specified threshold. Our algorithm can detect e-approximate frequent data items on data stream using O(e-1) memory
Shan Zhang, Ling Chen, Li Tu
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Maximum likelihood estimation of the K factor in ricean fading channels
IEEE Communications Letters, 2005Estimation of the K factor in a Ricean fading channel is studied. Unlike most previous estimators which employ exclusively samples of the fading envelope, new maximum likelihood estimators that use samples of both the fading envelope and the fading phase, or samples of the fading phase only, are derived and examined.
null Yunfei Chen, N.C. Beaulieu
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