DocumentCode :
2225780
Title :
Comparison of the conjugate gradient method to the method of recursive least square in terms of convergence rate
Author :
Choi, Seungwon ; Lee, Sang Seol
Author_Institution :
Dept. of Telecommun. Eng., Hanyang Univ., Seoul, South Korea
fYear :
1993
fDate :
18-20 May 1993
Firstpage :
905
Lastpage :
908
Abstract :
The convergence speed of the conjugate gradient method (CGM) is compared to that of the Kalman method. From simulations, the required computation time of CGM is about 79%-101% of that of the Kalman method. All the parameter values are set in both methods such that the performance of the receiving array is acceptable for land mobile communications. The main factor that causes the computation time to increase in the Kalman method is updating the inverse subcorrelation matrix. The main reason the CGM is superior to conventional algorithms is that the optimal weights are obtained in P steps in any signal environment
Keywords :
Kalman filters; array signal processing; computational complexity; conjugate gradient methods; convergence of numerical methods; land mobile radio; least squares approximations; matrix inversion; recursive estimation; Kalman method; computation time; conjugate gradient method; convergence speed; inverse subcorrelation matrix; land mobile communications; optimal weights; performance; receiving array; recursive least square; simulations; Adaptive algorithm; Adaptive arrays; Convergence; Gradient methods; Least squares methods; Mobile communication; Sampling methods; Sensor arrays; User-generated content; Wideband;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference, 1993., 43rd IEEE
Conference_Location :
Secaucus, NJ
ISSN :
1090-3038
Print_ISBN :
0-7803-1267-8
Type :
conf
DOI :
10.1109/VETEC.1993.510957
Filename :
510957
Link To Document :
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