Spatial process mining generates event logs from ceiling-camera detections and uses a HITS-style ranking of process nodes to identify abnormal manufacturing cycles.
Dynamical systems for eigenvalue problems of axisymmetric matrices with positive eigenvalues
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abstract
We consider the eigenvalues and eigenvectors of an axisymmetric matrix$A$ with some special structures. We propose S-Oja-Brockett equation $\frac{dX}{dt}=AXB-XBX^TSAX,$ where $X(t) \in {\mathbb R}^{n \times m}$ with $m \leq n$, $S$ is a positive definite symmetric solution of the Sylvester equation $A^TS = SA$ and $B$ is a real positive definite diagonal matrix whose diagonal elements are distinct each other, and show the S-Oja-Brockett equation has the global convergence to eigenvalues and its eigenvectors of $A$.
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Spatial Process Mining
Spatial process mining generates event logs from ceiling-camera detections and uses a HITS-style ranking of process nodes to identify abnormal manufacturing cycles.