Title :
Generalized autoregressive spectrum estimation algorithm based on particles sward optimization
Author :
Song Zhijie ; Wang qiaoying ; Wang Liang
Author_Institution :
Dept. of Ocean Technol., Ocean Univ. of China, Qingdao, China
Abstract :
In this paper, an intelligent optimal algorithm of generalized AR spectrum estimation (GAR) based on Particles Sward Optimum (PSO) is presented. After the model of GAR spectrum estimation suitable for numerical optimum is established using the error estimator in Burg algorithm, GAR algorithm is developed based on PSO. The results of its numerical simulation results are given and discussed. In contrast to Burg algorithm, GAR shows its better performance of spectrum estimation in the gain of ratio of signal to noise (SNR), frequency shift, spectrum splitting and frequency resolution at the cost of computational quantity.
Keywords :
autoregressive processes; estimation theory; particle swarm optimisation; signal resolution; spectral analysis; Burg algorithm; GAR algorithm; GAR spectrum estimation; error estimator; frequency resolution; frequency shift; generalized AR spectrum estimation; generalized autoregressive spectrum estimation; intelligent optimal algorithm; numerical optimum; particles sward optimization; signal to noise ratio; spectrum splitting; Algorithm design and analysis; Computational modeling; Estimation; Numerical models; Signal processing algorithms; Signal to noise ratio; Spectral analysis; Burg algorithm; PSO; spectrum estimation;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584131
