An improved method for inference of piecewise linear systems by detecting jumps using derivative estimation

Date

2009-08-01

Author

Selcuk, A. M.
Öktem, Hüseyin Avni

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Inference of dynamical systems using piecewise linear models is a promising active research area. Most of the investigations in this field have been stimulated by the research in functional genomics. In this article we study the inference problem in piecewise linear systems. We propose first identifying the state transitions by detecting the jumps of the derivative estimates, then finding the guard conditions of the state transitions (thresholds) from the values of the state variables at the state transition time and finally using the conventional gene regulatory network inference methods to infer the regulatory relations. This approach does not require a priori information or assumption on the guard conditions and provides robustness to environmental or measurement noise underlined by the used jump detection filter. We discuss the particular problems where the suggested method can improve the efficiency and demonstrate the results on a comparative basis.

Subject Keywords

Control and Systems Engineering, Analysis, Computer Science Applications

URI

https://hdl.handle.net/11511/38665

Journal

NONLINEAR ANALYSIS-HYBRID SYSTEMS

DOI

https://doi.org/10.1016/j.nahs.2009.01.006

Collections

Department of Biology, Article

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Citation Formats

A. M. Selcuk and H. A. Öktem, “An improved method for inference of piecewise linear systems by detecting jumps using derivative estimation,” NONLINEAR ANALYSIS-HYBRID SYSTEMS, pp. 277–287, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38665.