원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.8 No.5
2014.05
pp.231-242
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this research we investigate condition numbers obtained from least squares estimation for a car-trailer system to characterize estimation performance. In this case, we can select better parameter estimation methods or well-posed measured data sets for the car-trailer system using condition numbers. We calculate condition numbers from several different linear model-based least squares methods which use four linear regression models and three least squares methods to estimate trailer parameters. We also consider three different observed data sets in ideal and non-ideal sensor scenarios for simulation tests.
목차
Abstract
1. Introduction
2. Least Squares Techniques
2.1. Least Squares Techniques: OLS1, OLS2, and TLS
2.2. Condition Number
3. Linear Regression Model
3.1. Exact Model (EM)
3.2. Prediction Model (PM)
4. Estimation Methods
5. Simulation Results and Discussion
6. Conclusion
Acknowledgements
References
1. Introduction
2. Least Squares Techniques
2.1. Least Squares Techniques: OLS1, OLS2, and TLS
2.2. Condition Number
3. Linear Regression Model
3.1. Exact Model (EM)
3.2. Prediction Model (PM)
4. Estimation Methods
5. Simulation Results and Discussion
6. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보