کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
564126 | 875570 | 2012 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Mean square convergence analysis for kernel least mean square algorithm Mean square convergence analysis for kernel least mean square algorithm](/preview/png/564126.png)
In this paper, we study the mean square convergence of the kernel least mean square (KLMS). The fundamental energy conservation relation has been established in feature space. Starting from the energy conservation relation, we carry out the mean square convergence analysis and obtain several important theoretical results, including an upper bound on step size that guarantees the mean square convergence, the theoretical steady-state excess mean square error (EMSE), an optimal step size for the fastest convergence, and an optimal kernel size for the fastest initial convergence. Monte Carlo simulation results agree with the theoretical analysis very well.
► Mean-square convergence analysis for KLMS is carried out.
► An upper bound on step size is derived.
► Theoretical steady-state EMSE is obtained.
► Step size for the fastest convergence speed is derived.
► Kernel size for the fastest initial convergence is studied.
Journal: Signal Processing - Volume 92, Issue 11, November 2012, Pages 2624–2632