Kernel Estimation of Volterra Using an Adaptive Artificial Bee Colony Optimization and Its Application to Speech Signal Multi-Step Prediction

In order to solve parameters selection problem when applying recursive least square (RLS), least mean square (LMS) or normalized LMS (NLMS) algorithms to estimate kernels of second-order Volterra filter (SOVF), a novel adaptive gbest-guide artificial bee colony (AGABC) optimization algorithm is used...

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Bibliographic Details
Main Authors: Yumei Zhang, Yuying Rong, Chengling Yan, Jiangshan Liu, Xiaojun Wu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8565844/