Mazimum Entropy Spectral Estimation Based on Accelerating Genetic Algorithm
The purpose of this paper was to solve the problems of spectral peak shifting and line splitting existing in Burgs Maximum Entropy Spectral Analysis method (MESA), to enhance the resolution of entropy spectral, and to increase the adaptability of spectral estimation algorithm to signal length, signal noise ratio and initial phase. A method of accelerating Genetic algorithm based maximum Entropy Spectral estimation method (GES) was proposed, where accelerating genetic algorithm was used to optimize the parameters of MESA and the four equivalent conditions of MESA were used as objective function. Three typical simulation cases indicated that the phenomenon of spectral peak shifting and line splitting were absent in the frequency spectral estimated by GES, and the ability to discriminate two closed frequency was improved. Compared with the traditional MESA methods, GES has good performances in signal processing.
mazimum entropy spectral estimation Burg’s algorithm spectral peak shifting spectral line splitting accelerating genetic algorithm
ZHANG Ming ZHANG Jian-yun JIN Ju-liang WANG Guo-qing HE Rui-min
State Key Laboratory of Hydrology-water Resources and Hydraulic Engineering, Hohai University, Nanji Research Center for Climate Change, MWR, Nanjing, 210029, China Nanjing Hydraulic Research Institute School of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
4184-4189
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）