Title : 
The improved algorithms to estimate α of alpha stable distribution based on empirical characteristic function
         
        
            Author : 
Guangrong, Xia ; Xingzhao, Liu
         
        
            Author_Institution : 
Dept. of Electron. Eng., Shanghai Jiao Tong Univ., China
         
        
        
        
        
        
            Abstract : 
The estimation of characteristic exponent α is the most important step for the parameter estimation of symmetric α stable distribution. For lack of closed form of probability density function (pdf), classical methods are no longer available. In this paper improved algorithms based on the empirical characteristic function are proposed to solve this problem under the conditions of short data samples. Simulations show that the proposed algorithms are robust and they are more efficient and applicable than the conventional ones.
         
        
            Keywords : 
numerical stability; parameter estimation; probability; signal sampling; characteristic exponent; empirical characteristic function; parameter estimation; short data samples; symmetric alpha stable distribution; Equations; Gaussian distribution; Interference; Maximum likelihood estimation; Parameter estimation; Power engineering and energy; Probability density function; Probability distribution; Random variables; Robustness;
         
        
        
        
            Conference_Titel : 
Signal Processing, 2002 6th International Conference on
         
        
            Print_ISBN : 
0-7803-7488-6
         
        
        
            DOI : 
10.1109/ICOSP.2002.1181020