Efficient total least squares method for system modeling using minor component analysis
Tóm tắt
We present two algorithms to solve the total least-squares (TLS) problem. The algorithms are on-line with O(N/sup 2/) and O(N) complexity. The convergence of the algorithms is significantly faster than the traditional methods. A mathematical analysis of convergence is also provided along with simulations to substantiate the claims. We also apply the TLS algorithms for FIR system identification with known model order in the presence of noise.
Từ khóa
#Least squares methods #Modeling #Signal processing algorithms #Parameter estimation #Algorithm design and analysis #Convergence #Vectors #Analytical models #Neural engineering #LaboratoriesTài liệu tham khảo
haykin, 1986, Adaptive Filter Theory
rao, 2000, A Fast On-line Algorithm for PCA and its Convergence Characteristics, Proc IEEE Workshop Neural Networks Signal Process, 299
rao, 2000, Algorithms For Eigendecomposition and Time Series Segmentation
rao, 0, The CNEL rule: A Novel On-line Algorithm for Principal Component Analysis
10.1109/TAC.1977.1101561
10.1007/978-3-642-75894-2
10.1016/0893-6080(95)91644-9
10.1109/78.700968
diamantaras, 1996, Principal Component Neural Networks, Theory and Applications
moon, 1999, Mathematical Methods and Algoritbms for Signal Processing
golub, 1989, Matrix Cemputatlens
10.1109/78.275601
10.1109/72.839022
10.1109/78.348123
10.1016/0893-6080(92)90006-5
luo, 1997, A Minor Subspace Analysis Algorithm, IEEE Trans Neural Networks, 8
gao, 1994, A Constrained Anti-Hebbian Learning Algorithm for Total Least-Squares Estimation with Applications to Adaptive FIR and IIR Filtering, IEEE Trans Circuits and Systems-II Analog and Digital Signal Processing, 41
deprettere, 1988, Applications and Architectures, SVD And Signal Processing - Algorithms
10.1109/82.544031