Convex Optimization In Identification Of Stable Non-Linear State Space Models

Details Convex Optimization In Identification Of Stable Non-Linear State Space Models Convex Optimization In Identification Of Stable Non-Linear State Space Models

2010-09-09

arxiv.org/abs/1009.1670v1

Mathematics

Optimization and Control

9 pages, 2 figure, elaboration of same-title paper in 49th IEEE Conference on Decision and Control

Scientific paper

A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined as a measure of robustness of the simulation error with respect to equation errors. Basic definitions and analytical results are presented. The utility of the method is illustrated on a simple simulation example as well as experimental recordings from a live neuron.

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