Adaptive Fourier linear combiner based on modified least mean Kurtosis algorithm for the processing of sinusoidal signals

Mengüç E. C.

Transactions of the Institute of Measurement and Control, cilt.43, sa.5, ss.1039-1047, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 43 Sayı: 5
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1177/0142331219889171
  • Dergi Adı: Transactions of the Institute of Measurement and Control
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1039-1047
  • Anahtar Kelimeler: Fourier linear combiner, least mean kurtosis, sinusoidal signals, pathological hand tremor, PHYSIOLOGICAL TREMOR, FREQUENCY ESTIMATION, NOTCH FILTER, DESIGN
  • Kayseri Üniversitesi Adresli: Evet

Özet

© The Author(s) 2019.This study introduces an adaptive Fourier linear combiner (FLC) based on a modified least mean kurtosis (LMK) algorithm in order to effectively process sinusoidal signals, which we call FLC-LMK algorithm. In the design procedure of the proposed FLC-LMK algorithm, the classical kurtosis-based cost function is first modified for only sinusoidal signal distributions instead of Gaussian. Then, the FLC-LMK algorithm is derived from the minimization of this cost function and thus updates the weight coefficients of the FLC structure so as to directly process sinusoidal signals. Moreover, in this study, the convergence in the mean of the proposed FLC-LMK algorithm is analysed in order to determine the lower and upper bounds of its step size parameter. The most important contributions of the use of the proposed algorithm in the FLC structure are that it increases the convergence rate, decreases the steady-state error level and also has a robust behaviour against sinusoidal signal distributions due to its modified cost function. The performance of the proposed FLC-LMK algorithm is evaluated on the synthetic and real-world pathological hand tremor data by comparing with that of the FLC based on the classical least mean square (LMS) (FLC-LMS) algorithm. The simulation results support the mentioned properties of the proposed FLC-LMK algorithm.