# Learning Complexity Dimensions for a Continuous-Time Control System

@article{Kuusela2004LearningCD, title={Learning Complexity Dimensions for a Continuous-Time Control System}, author={Pirkko Kuusela and Daniel Ocone and Eduardo Sontag}, journal={ArXiv}, year={2004}, volume={math.OC/0012163} }

This paper takes a computational learning theory approach to a problem of linear systems identification. It is assumed that inputs are generated randomly from a known class consisting of linear combinations of k sinusoidals. The output of the system is classified at some single instant of time. The main result establishes that the number of samples needed for identification with small error and high probability, independently from the distribution of inputs, scales polynomially with n, the…

## 5 Citations

Sample Complexity Lower Bounds for Linear System Identification

- Computer Science, Mathematics2019 IEEE 58th Conference on Decision and Control (CDC)
- 2019

This paper establishes problem-specific sample complexity lower bounds for linear system identification problems, and really captures the identification hardness specific to the system.

Input Classes for Identifiability of Bilinear Systems

- MathematicsIEEE Transactions on Automatic Control
- 2009

The main results are that step inputs are not sufficient, nor are single pulses, but the family of all pulses (of a fixed amplitude but varying widths) do suffice for identification.

Input Classes for Identification of Bilinear Systems

- Mathematics
- 2006

This paper asks what classes of input signals are sufficient in order to completely identify the input/output behavior of generic bilinear systems. The main results are that step inputs are not…

Remarks on Input Classes for Identification of Bilinear Systems

- Mathematics2007 American Control Conference
- 2007

The main results are that step inputs are not sufficient, nor are single pulses, but the family of all pulses (of a fixed amplitude but varying widths) do suffice for identification.

O C ] 2 0 O ct 2 00 6 Input Classes for Identification of Bilinear Systems

- Mathematics
- 2006

This paper asks what classes of input signals are sufficient in order to completely identify the input/output behavior of generic bilinear systems. The main results are that step inputs are not…

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