On the stochastic modeling of the LMS algorithm operating with bilinear forms

2021 ◽  
pp. 103359
Author(s):  
Khaled Jamal Bakri ◽  
Eduardo Vinicius Kuhn ◽  
Rui Seara ◽  
Jacob Benesty ◽  
Constantin Paleologu ◽  
...  
2021 ◽  
Author(s):  
Khaled Jamal Bakri ◽  
Eduardo Vinicius Kuhn ◽  
Marcos Vinicius Matsuo ◽  
Rui Seara ◽  
Jacob Benesty ◽  
...  

2008 ◽  
Vol 56 (5) ◽  
pp. 1840-1852 ◽  
Author(s):  
Elen Macedo Lobato ◽  
Orlando JosÉ Tobias ◽  
Rui Seara

Algorithms ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 211 ◽  
Author(s):  
Laura-Maria Dogariu ◽  
Silviu Ciochină ◽  
Constantin Paleologu ◽  
Jacob Benesty

The system identification problem becomes more challenging when the parameter space increases. Recently, several works have focused on the identification of bilinear forms, which are related to the impulse responses of a spatiotemporal model, in the context of a multiple-input/ single-output system. In this framework, the problem was addressed in terms of the Wiener filter and different basic adaptive algorithms. This paper studies two types of algorithms tailored for the identification of such bilinear forms, i.e., the Kalman filter (along with its simplified version) and an optimized least-mean-square (LMS) algorithm. Also, a comparison between them is performed, which shows interesting similarities. In addition to the mathematical derivation of the algorithms, we also provide extensive experimental results, which support the theoretical findings and indicate the good performance of the proposed solutions.


Author(s):  
Laura-Maria Dogariu ◽  
Silviu Ciochina ◽  
Constantin Paleologu ◽  
Jacob Benesty ◽  
Pablo Piantanida
Keyword(s):  

2009 ◽  
Vol 19 (12) ◽  
pp. 1171-1191 ◽  
Author(s):  
Mark Archambault

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