Adaptive Algorithm Performance Summary

2011 ◽  
pp. 365-369
2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Alimorad Mahmoudi

This paper deals with the problem of two-dimensional autoregressive (AR) estimation from noisy observations. The Yule-Walker equations are solved using adaptive steepest descent (SD) algorithm. Performance comparisons are made with other existing methods to demonstrate merits of the proposed method.


2003 ◽  
Vol 16 (3) ◽  
pp. 377-387
Author(s):  
Ljubisa Stankovic

Analysis of the algorithm for the mean square error minimization, through the bias-to-variance ratio optimization, is performed. This algorithm is based on the confidence intervals intersection. It does not require explicit knowledge of the estimation bias. The algorithm performance and reliability for various kinds of noise in the estimation are studied.


2018 ◽  
Vol 138 (11) ◽  
pp. 1355-1361
Author(s):  
Masaki Kobayashi ◽  
Naoto Sasaoka ◽  
Yoshio Itoh

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