Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài:Research Article Two-Dimensional Harmonic Retrieval in Correlative Noise Based on Genetic Algorithm | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 569371 10 pages doi 2010 569371 Research Article Two-Dimensional Harmonic Retrieval in Correlative Noise Based on Genetic Algorithm Sun-Yong Wu 1 2 Gui-Sheng Liao 1 and Zhi-Wei Yang1 1 National Lab of Radar Signal Processing Xidian University Xi an Shanxi 710071 China 2 Department of Computational Science and Mathematics Guilin University of Electronic Technology Guilin Guangxi 541004 China Correspondence should be addressed to Sun-Yong Wu wusunyong121991@ and Gui-Sheng Liao gsliao@ Received 30 December 2009 Revised 13 May 2010 Accepted 16 June 2010 Academic Editor Ljubisa Stankovic Copyright 2010 Sun-Yong Wu et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. We propose a niche Genetic algorithm GA for the two-dimensional 2D harmonic retrieval in the presence of correlative zero-mean multiplicative and additive noise. Firstly we introduce a 2D fourth-order time-average moment spectrum which has extremum values at the harmonic frequencies. On this basis the problem of harmonic retrieval is treated as a problem of finding the extremum values for which the niche GA is resorted. Utilizing the global searching ability of the GA this method can improve the frequency estimation performance. The effectiveness of the proposed algorithm is demonstrated through computer simulations. 1. Introduction 2D harmonic retrieval is of interest in signal processing such as sonar radar geophysics and radio astronomy. In the case of additive noise some high-resolution techniques such as the 2D MUSIC 1 the 2D MEMP 2 and the 2D ESPRIT method 3 have been developed from their 1D versions. Of these algorithms the ESPIRIT algorithm is more effective as it does not require to search for the peak value
