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We developed a model based on Laguerre expansion technique, LET, to identify the dynamic SEMG force relation and investigate the presence of fatigue through kernel analysis.
In this study, we used a rapid event-related design and Volterra kernel analysis to assess the effect of a 200 mg oral dose of caffeine on the linearity of the visual BOLD response.
Since the results of automated characterisation of landscapes from DEMs are influenced by the extent being considered, the resolution of the source DEM and the size of the kernel (analysis window) used for processing, we have developed a tool to allow GIS users to flexibly apply several multi-scale analysis methods to parameterise and classify a DEM into discrete land surface units.
Settlement Kernel analysis result shows clusters of settlement distribute throughout the city.
Fig. 20 Comparison of the SHT's size between FusedVS analysis and Kernel analysis.
Fig. 19 Comparison of construction time between FusedVS analysis and Kernel analysis.
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The coordinate-based meta-analysis was performed using a Multilevel Kernel Density Analysis (MKDA 2.
Kernel discriminant analysis, which employs the kernel technique to perform linear discriminant analysis in a high-dimensional feature space, is developed to extract the significant nonlinear features which maximise the between-class variance and minimise the within-class variance.
We will submit our wheat samples for total kernel N analysis.
Kernel discriminant analysis (KDA) is effective to extract nonlinear discriminative features of input samples using the kernel trick.
This paper proposes a performance-driven distributed monitoring scheme that incorporates kernel principal analysis (KPCA) and Bayesian diagnosis system for large-scale nonlinear processes.
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