Nonlinear Multifunctional Sensor Signal Reconstruction Based on Total Least Squares
The least squares method is often used to estimate the parameters in multi-functional sensor signal reconstruction. If the data has been contaminated, the computational result of the method turns out to be insignificant. Two methods presented in this paper are suitable for different nonlinear conditions, which are based on the combination of the total least squares algorithm with the local linearization strategy and Stone-Weierstrass theorem. The two methods evaluate both the sensor output bias and its input error. The results of emulation and theory analysis indicate that the proposed algorithms are more accurate and reliable for signal reconstruction.
X Liu J W Sun D Liu
Dept.of Automatic Measurement and Control, Harbin Institute of Technology, Harbin 150001, China
国际会议
第四届仪器科学与技术国际会议( 4th International Symposium on Instrumentation and Science and Tcchnology)
哈尔滨
英文
281-286
2006-08-08（万方平台首次上网日期，不代表论文的发表时间）