Add to ORKGOn convergence of the normalized alternating least squares (ALS) algorithm. - Augsburg, 1983. - 14 Bl. - (Arbeitspapiere zur mathematischen Wirtschaftsforschung ; 68
This paper studies the convergence behaviors of the noise-constrained normalized least mean squares ...
The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potent...
In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares...
On convergence of the normalized alternating least squares (ALS) algorithm. - Augsburg, 1983. - 14 B...
In principal components analysis (PCA) of mixture of quantitative and qual-itative data, we require ...
Several models in data analysis are estimated by minimizing the objective function defined as the re...
This paper studies the convergence behaviors of the normalized least mean square (NLMS) and the norm...
This paper compares the convergence rate performance of the Normalized Least-Mean-Square (or NLMS) a...
The normalized least mean-fourth (NLMF) algorithm is presented in this work and shown to have potent...
It is well-known that good initializations can improve the speed and accuracy of the solutions of ma...
Shows that the NLMS (normalized least-mean-square) algorithm is a potentially faster converging algo...
This thesis is being archived as a Digitized Shelf Copy for campus access to current students and st...
This work repots results of the convergence analysis of the normalized sign-sign least mean square (...
In this work, the ε-normalized sign regressor least mean mixed-norm (NSRLMMN) adaptive algorithm is ...
In this paper, we discuss the acceleration of the regularized alternating least-squares (RALS) algor...
This paper studies the convergence behaviors of the noise-constrained normalized least mean squares ...
The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potent...
In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares...
On convergence of the normalized alternating least squares (ALS) algorithm. - Augsburg, 1983. - 14 B...
In principal components analysis (PCA) of mixture of quantitative and qual-itative data, we require ...
Several models in data analysis are estimated by minimizing the objective function defined as the re...
This paper studies the convergence behaviors of the normalized least mean square (NLMS) and the norm...
This paper compares the convergence rate performance of the Normalized Least-Mean-Square (or NLMS) a...
The normalized least mean-fourth (NLMF) algorithm is presented in this work and shown to have potent...
It is well-known that good initializations can improve the speed and accuracy of the solutions of ma...
Shows that the NLMS (normalized least-mean-square) algorithm is a potentially faster converging algo...
This thesis is being archived as a Digitized Shelf Copy for campus access to current students and st...
This work repots results of the convergence analysis of the normalized sign-sign least mean square (...
In this work, the ε-normalized sign regressor least mean mixed-norm (NSRLMMN) adaptive algorithm is ...
In this paper, we discuss the acceleration of the regularized alternating least-squares (RALS) algor...
This paper studies the convergence behaviors of the noise-constrained normalized least mean squares ...
The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potent...
In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares...