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System identification for chaotic integrate‐and‐fire dynamics
Author(s) -
Sauer Tim
Publication year - 1997
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/(sici)1098-111x(199704)12:4<255::aid-int1>3.0.co;2-n
Subject(s) - chaotic , computer science , observable , identification (biology) , system identification , series (stratigraphy) , dynamical systems theory , spike train , spike (software development) , system dynamics , state (computer science) , dynamical system (definition) , statistical physics , interval (graph theory) , control theory (sociology) , algorithm , artificial intelligence , data mining , mathematics , physics , paleontology , botany , software engineering , control (management) , quantum mechanics , combinatorics , measure (data warehouse) , biology
We discuss applications of the fact that dynamical state information can be reconstructed from a series of interspike interval (ISI) measurements. This system analysis allows system identification and prediction from spike train history. Secondly, using this reconstruction, unstable periodic trajectories of the underlying system can be controlled by small changes in a system parameter. The underlying assumption is an integrate‐and‐fire model coupling the dynamical system to the observable spike train. © 1997 John Wiley & Sons, Inc.