Results 221 to 230 of about 14,159 (246)
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Kernel-based Nonlinear Fit with Total Least Square(TLS) Method

2007 Chinese Control Conference, 2006
In this paper, on the basis of linear fit in the total least square(TLS) method sense, we proposed a method of nonlinear fit in the TLS method sense via kernel representation. Namely, by using an appropriate kernel function, the problems of nonlinear fit can be transformed to the problems of linear fit without paying the computational penalty and ...
Hu Guanghua, Fu Guanghui
openaire   +1 more source

Application of total least squares (TLS) to the design of sparse signal representation dictionaries

Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002., 2003
Sparse signal representation has been the subject of much research in recent years in a variety of applications. We address the problem of learning a dictionary of waveforms from a given set of data signals, which may then be used to provide efficient and meaningful signal decompositions.
S.F. Cotter, B.D. Rao
openaire   +1 more source

Robust Recursive TLS (Total Least Square) Method Using Regularized UDU Decomposed for FNN (Feedforward Neural Network) Training

2005
We present a robust recursive total least squares (RRTLS) algorithm for multilayer feed-forward neural networks. So far, recursive least squares (RLS) has been successfully applied to training multilayer feed-forward neural networks. However, if input data has additive noise, the results from RLS could be biased.
JunSeok Lim, Nakjin Choi, KoengMo Sung
openaire   +1 more source

Interference Suppression with Total Least Square (TLS) Algorithm and Constant Modulus Algorithm (CMA)

The International Conference on Electrical Engineering, 2008
K. El-Barbary   +3 more
openaire   +1 more source

Adjustment of Real-time Kinematic-Global Positioning System (RTK-GPS) Survey Data: A Comparative Performance Analysis of the Back Propagation Artificial Neural Network (BPANN) and the Total Least Squares (TLS) Techniques

This study seeks to conduct an empirical evaluation of the performances of two soft computing methodologies comprising the Levenberg-Marquardt Back Propagation Artificial Neural Network (LMBPANN) and the Bayesian Regularisation Backpropagation Artificial Neural Network (BRBPANN).
Larbi, Edwin Kojo   +2 more
openaire   +1 more source

Partial Discharge Location Algorithm Based on Total Least-Squares With Matérn Kernel in Cable Systems

IEEE Transactions on Industrial Informatics, 2023
Lu Lu, Kai Zhou, Zhu Guangya
exaly  

Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling

IEEE Transactions on Signal Processing, 2011
Hao Zhu   +2 more
exaly  

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