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Binbin Li, Bo Lu, Xiping Kou, Yang Shi, Li Yu, Hongtao Guo, Binbin Lv and Kaichun Zeng
To address the contradiction between the convergence error and convergence rate in the LMS algorithm, this study proposes a variable-step-size adaptive filter algorithm with a momentum term based on the logistic function. First, the normalization LMS alg...
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Yongzhou Li, Di Sun, Zejun Wu and Kunyuan Zhang
With the development of combined cycle engines, it is urgent to estimate more quickly and accurately the flow capture capacity and starting performance of variable geometry inlets over a wide Mach number range. Based on the flow field and parameter fitti...
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Raoul R. Nigmatullin and Jocelyn Sabatier
This work was greatly influenced by the opinions of one of the authors (JS), who demonstrated in a recent book that it is important to distinguish between ?fractal models? and ?fractal? (power-law) behaviors. According to the self-similarity principle (S...
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Sean McCarthy, Summer Crawford, Christopher Wood, Mark D. Lewis, Jason K. Jolliff, Paul Martinolich, Sherwin Ladner, Adam Lawson and Marcos Montes
Here we present a machine-learning-based method for utilizing traditional ocean-viewing satellites to perform automated atmospheric correction of nanosatellite data. These sensor convolution techniques are required because nanosatellites do not usually p...
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Panos Nikitas and Efthymia Nikita
This paper assesses algorithms proposed for constructing confidence ellipses in multidimensional scaling (MDS) solutions and proposes a new approach to interpreting these confidence ellipses via hierarchical cluster analysis (HCA). It is shown that the m...
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