On Computing the Inverse of Vandermonde Matrix via Synthetic Divisions

2018 ◽  
pp. 121-128
Author(s):  
Yiu-Kwong Man
Keyword(s):  
Vandermonde Matrix

scholarly journals Learning Coefficient of Vandermonde Matrix-Type Singularities in Model Selection

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 561
Author(s):  
Miki Aoyagi
Keyword(s):  
Model Selection ◽  
Information Criteria ◽  
Learning Systems ◽  
Vandermonde Matrix ◽  
Selection Methods ◽  
Learning Models ◽  
Matrix Type ◽  
Log Canonical Threshold ◽  
Log Canonical ◽  
Blowing Up

In recent years, selecting appropriate learning models has become more important with the increased need to analyze learning systems, and many model selection methods have been developed. The learning coefficient in Bayesian estimation, which serves to measure the learning efficiency in singular learning models, has an important role in several information criteria. The learning coefficient in regular models is known as the dimension of the parameter space over two, while that in singular models is smaller and varies in learning models. The learning coefficient is known mathematically as the log canonical threshold. In this paper, we provide a new rational blowing-up method for obtaining these coefficients. In the application to Vandermonde matrix-type singularities, we show the efficiency of such methods.

scholarly journals Research on the method of fast inverse realisation of Vandermonde matrix based on FPGA

2019 ◽  
Vol 2019 (20) ◽  
pp. 6848-6851
Author(s):  
Lei Chen ◽  
Liang Chen ◽  
BingY Li
Keyword(s):  
Vandermonde Matrix

The Generalized Vandermonde Matrix

1984 ◽  
Vol 57 (1) ◽  
pp. 15-21 ◽  
Author(s):  
Dan Kalman
Keyword(s):  
Vandermonde Matrix

On the Vandermonde Matrix

1989 ◽  
Vol 96 (10) ◽  
pp. 921 ◽  
Author(s):  
Joseph J. Rushanan
Keyword(s):  
Vandermonde Matrix
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