Title :
Total Least Squares method for sine fitting
Author :
Wang Xin ; Xu Yuanyuan
Author_Institution :
Inst. of Meas. & Process Control, Jiangnan Univ., Wuxi, China
Abstract :
Sine fitting is a fundamental task in many test and measurement systems. Total Least Squares (TLS) is an extension of the usual least squares method: it allows dealing also with uncertainties on the sensitivity matrix. A sine fitting algorithm based on TLS are employed to filter the sampled sequences of sine signals, eliminating ill effects on the measurement accuracy caused by noises (including the harmonic distortion and quantization error). Experiments show that the given noised sine signals can be estimated accurately after uniform sampling, and the sampling time should be considered carefully.
Keywords :
harmonic distortion; least squares approximations; measurement systems; quantisation (signal); signal sampling; harmonic distortion; measurement accuracy; quantization error; sensitivity matrix; sine fitting; total least squares method; Artificial neural networks; Quantization error; SVD decomposition; Sampling time; Sine fitting; Total least squares;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579232