title: Detection of fixed points in spatiotemporal signals by a clustering method.
abstract: We present a method to determine fixed points in spatiotemporal signals. The method combines a clustering algorithm and a nonlinear analysis method fitting temporal dynamics. A 144-dimensional simulated signal, similar to a Kueppers-Lortz instability, is analyzed and its fixed points are reconstructed.
authors.affiliation: Max Planck Institute of Cognitive Neuroscience, Leipzig, Germany. hutt@cns.mpg.de
authors.forename: A
authors.initials: A
authors.lastname: Hutt
authors.forename: M
authors.initials: M
authors.lastname: Svensén
authors.forename: F
authors.initials: F
authors.lastname: Kruggel
authors.forename: R
authors.initials: R
authors.lastname: Friedrich
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008959:Models, Neurological