سال انتشار: ۱۳۹۱

محل انتشار: بیستمین کنفرانس مهندسی برق ایران

تعداد صفحات: ۵

نویسنده(ها):

Mohammad Shams Esfand Abadi – Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
Ali-Reza Danaee –

چکیده:

Selective partial update (SPU) strategy in adaptive filter algorithms is used to reduce the computational complexity. In this paper we apply the SPU Normalized Least Mean Squares algorithms (SPU-NLMS) for distributed estimation problem based on incremental strategy in a incremental network. The distributed SPU-NLMS (dSPUNLMS) reduces the computational complexity while it’s performance is close to the dNLMS. We demonstrate the good performance of dSPU-NLMS in both convergence speed and steady-state mean square error