DocumentCode :
2429030
Title :
Recursive least squares constant modulus algorithm based on the QR decomposition
Author :
Shuyan, Wang ; Renbiao, Wu ; Qingyan, Shi
Author_Institution :
Tianjin Key Lab. for Adv. Signal Process., Civil Aivation Univ. of China, Tianjin
fYear :
2008
fDate :
7-11 June 2008
Firstpage :
159
Lastpage :
162
Abstract :
A novel QR-RLS constant modulus algorithm called QR-RLS-CMA is proposed. Its potential advantages include numerical stability, computational efficiency and a fast convergence rate. Simulations are performed to compare the convergence performance and the blind extracting ability of the proposed QR-RLS-CMA to the conventional SGD-CMA for adaptive CMA array. Results indicate that the QR-RLS-CMA has a much faster convergence rate than the SGD-CMA in the initial convergence phase. It illustrates the effectiveness of the proposed method.
Keywords :
least squares approximations; matrix decomposition; numerical stability; recursive estimation; signal processing; QR decomposition; blind extracting ability; computational efficiency; numerical stability; recursive least squares constant modulus algorithm; Adaptive algorithm; Adaptive arrays; Computational efficiency; Computational modeling; Convergence of numerical methods; Frequency modulation; Least squares methods; Linear antenna arrays; Numerical stability; Signal processing algorithms; QR decomposition; QR-RLS-CMA; QRRLS; SGD-CMA; adaptive CMA array;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-2310-1
Electronic_ISBN :
978-1-4244-2311-8
Type :
conf
DOI :
10.1109/ICNNSP.2008.4590331
Filename :
4590331
Link To Document :
بازگشت