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Adaptive Forgetting Factor RLS Algorithm Based on Gradient of Inverse Correlation Matrix Applied to Human Motion Analysis

Authors
  • Hadi Sadoghi Yazdi
  • Seyed Ebrahim Hosseini
  • Mohammad Reza Mohammadi
Conference دوازدهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Abstract This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.
قیمت
  • برای اعضای سایت : 100,000 Rial
  • برای دانشجویان عضو انجمن : 20,000 Rial
  • برای اعضای عادی انجمن : 40,000 Rial

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