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Parametrized topological complexity of poset-stratified spaces.

Kohei Tanaka
Published in: Journal of applied and computational topology (2021)
In this paper, parametrized motion planning algorithms for a fiberwise space X → P over a poset P are studied. Such an algorithm assigns paths in a space X decomposed into subspaces with the index set P , that do not cross the boundaries of the separated regions. We compute the parametrized topological complexity of X → P , which is one less than the minimal number of local parametrized motion planning algorithms used for designing non-cross-border robot motions in X .
Keyphrases
  • machine learning
  • deep learning
  • high speed
  • mass spectrometry
  • neural network