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ICAPR
2005
Springer

Hierarchical Clustering of Dynamical Systems Based on Eigenvalue Constraints

10 years 4 months ago
Hierarchical Clustering of Dynamical Systems Based on Eigenvalue Constraints
Abstract. This paper addresses the clustering problem of hidden dynamical systems behind observed multivariate sequences by assuming an interval-based temporal structure in the sequences. Hybrid dynamical systems that have transition mechanisms between multiple linear dynamical systems have become common models to generate and analyze complex time-varying event. Although the system is a flexible model for human motion and behaviors, the parameter estimation problem of the system has a paradoxical nature: temporal segmentation and system identification should be solved simultaneously. The EM algorithm is a well-known method that solves this kind of paradoxical problem; however the method strongly depends on initial values and often converges to a local optimum. To overcome the problem, we propose a hierarchical clustering method of linear dynamical systems by constraining eigenvalues of the systems. Due to the constraints, the method enables parameter estimation of dynamical systems f...
Hiroaki Kawashima, Takashi Matsuyama
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICAPR
Authors Hiroaki Kawashima, Takashi Matsuyama
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