کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4973784 1451709 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Diffusion LMS algorithms with multi combination for distributed estimation: Formulation and performance analysis
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Diffusion LMS algorithms with multi combination for distributed estimation: Formulation and performance analysis
چکیده انگلیسی
We propose diffusion least-mean-square (LMS) algorithms that use multi-combination step. We allow each node in the network to use information from multi-hop neighbors to approximate a global cost function accurately. By minimizing this cost and dividing multi-hop range summation into 1-hop range combination steps, we derive new diffusion LMS algorithms. The resulting distributed algorithms consist of adaptation and multi-combination step. Multi combination allows each node to use information from non-adjacent nodes at each time instant, thereby reducing steady-state error. We analyzed the output to derive stability conditions and to quantify the transient and steady-state behaviors. Theoretical and experimental results indicate that the proposed algorithms have lower steady-state error compared to the conventional diffusion LMS algorithms. We also propose a new combination rule for the multi-combination step which can further improve the estimation performance of the proposed algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 71, December 2017, Pages 117-130
نویسندگان
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