Under a domination condition, real-analytic deformations of symplectomorphism products yield large robustly transitive sets and new non-uniformly-hyperbolic examples via blender-horseshoe perturbations and control-theory ideas.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
CNNs trained on speckle images from levitating TiO2 suspension microdroplets classify droplet diameter with better than 6% accuracy and provide useful discrimination for nanoparticle concentration and diameter, including simultaneous three-parameter classification.
citing papers explorer
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Robustly transitive behavior in symplectic dynamics
Under a domination condition, real-analytic deformations of symplectomorphism products yield large robustly transitive sets and new non-uniformly-hyperbolic examples via blender-horseshoe perturbations and control-theory ideas.
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Determination of Nanoparticle and Microdroplet Parameters in Levitating Microdroplets of Suspension by Speckle Image Analysis Using Convolutional Neural Networks
CNNs trained on speckle images from levitating TiO2 suspension microdroplets classify droplet diameter with better than 6% accuracy and provide useful discrimination for nanoparticle concentration and diameter, including simultaneous three-parameter classification.