Title :
A Normalized Minimum Error Entropy Stochastic Algorithm
Author :
Han, Seungju ; Rao, Sudhir ; Jeong, Kyu-Hwa ; Principe, Jose
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL
Abstract :
We propose in this paper the normalized minimum error entropy (NMEE). Following the same rational that lead to the normalized LMS, the weight update adjustment for minimum error entropy (MEE) is constrained by the principle of minimum disturbance. Unexpectedly, we obtained an algorithm that not only is insensitive to the power of the input, but is also faster than the MEE for the same misadjustment, and also that is less sensitive to the kernel size. We explain these results analytically, and through system identification simulations
Keywords :
least mean squares methods; minimum entropy methods; stochastic processes; normalized LMS; normalized minimum error entropy stochastic algorithm; system identification simulations; Computer errors; Convergence; Entropy; Error correction; Finite impulse response filter; Kernel; Least squares approximation; Stability; Stochastic processes; System identification;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1661349
