2010
DOI: 10.1007/s12555-010-0403-5
|View full text |Cite
|
Sign up to set email alerts
|

A computationally efficient approach for NN based system identification of a rotary wing UAV

Abstract: Neural Network (NN) models based on autoregressive structures have long been used for nonlinear system identification problems. Their application for on-line implementations, however require them to be trained within a prescribed time span, which is often related to the sampling time of the system. In this paper, we introduce a NN model that is embedded with a dimensionality reduction mechanism in order to reduce the size of the network. The dimensionality reduction is based on Principal Component Analysis (PC… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2012
2012
2017
2017

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
references
References 12 publications
0
0
0
Order By: Relevance