Paper Info
Title
The least mean kurtosis: Its steady state performance with gaussian and non-gaussian noise
Abstract
In this paper, the final mean square error (MSE) of the least mean kurtosis (LMK) adaptive algorithm is theoretically derived by applying the energy conservation adaptive filters and on the n-th order correlation theory. The behavior is compared with the conventional least mean square (LMS) algorithm. Our study shows that it is possible to adjust the performance of the LMK. It can even outperform the LMS.
Year
Venue
Keywords
2005
Seventh IASTED International Conference on Signal and Image Processing
steady state analysis,least mean kurtosis,a robust adaptive filter
Field
DocType
Citations 
Statistical physics,Gaussian random field,Gaussian,Noise spectral density,Steady state,Gaussian noise,Additive white Gaussian noise,Gaussian function,Mathematics,Kurtosis
Conference
1
PageRank 
References 
Authors
0.37
1
1
Name
Order
Citations
PageRank
Junibakti Sanubari142.23