Academic Journal

A variable step size least mean p-power adaptive filtering algorithm based on multi-moment error fusion

التفاصيل البيبلوغرافية
العنوان: A variable step size least mean p-power adaptive filtering algorithm based on multi-moment error fusion
المؤلفون: Boyu Zhu, Biao Wang, Banggui Cai, Yunan Zhu, Peng Chao, Zide Fang
المصدر: EURASIP Journal on Advances in Signal Processing, Vol 2023, Iss 1, Pp 1-15 (2023)
بيانات النشر: SpringerOpen, 2023.
سنة النشر: 2023
المجموعة: LCC:Telecommunication
LCC:Electronics
مصطلحات موضوعية: Impulsive noise, α-stable distribution, Adaptive filtering algorithm, Least mean p-power (LMP), Multi-moment error, Telecommunication, TK5101-6720, Electronics, TK7800-8360
الوصف: Abstract For the channel estimation problem under α-stable distributed impulse interference, the traditional fixed-step adaptive filtering cannot satisfy the fast convergence speed and low steady-state error at the same time, whereas the variable-step method is able to effectively solve this contradiction. This paper proposes an improved variable step-size least mean p-power adaptive algorithm that offers good robustness against impulsive noise. The proposed algorithm takes into account the linkage between the errors and uses the adjustment of the step size based on the errors of the current moment and the previous k moments, thus overcoming the problems of poor anti-noise performance and large steady-state fluctuations of the fixed-step size algorithm. This algorithm ensures that the step size does not change abruptly when the system is disturbed by impulse noise and can achieve a lower steady-state error. The simulation results show that the algorithm has better convergence than the traditional fixed step-size algorithm and the existing variable step-size algorithm under the interference of impulsive noise.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1687-6180
Relation: https://doaj.org/toc/1687-6180
DOI: 10.1186/s13634-023-01042-x
URL الوصول: https://doaj.org/article/b2625ee9dac84f9896999ac6650c8794
رقم الانضمام: edsdoj.b2625ee9dac84f9896999ac6650c8794
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:16876180
DOI:10.1186/s13634-023-01042-x