Sparse Normalized Least Mean Absolute Deviation Algorithm Based on Unbiasedness Criterion for System Identification With Noisy Input

Sparse Normalized Least Mean Absolute Deviation Algorithm Based on Unbiasedness Criterion for System Identification With Noisy Input

In order to solve the system identification problems, the normalized least mean absolute deviation (NLMAD) algorithm was developed as an effective and robust method. In this paper, aiming at the system identification problems with sparsity characteristic, and taking the advantage of the NLMAD algori...

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Bibliographic Details
Main Authors: Wentao Ma, Ning Li, Yuanhao Li, Jiandong Duan, Badong Chen
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Normalized least mean absolute deviation
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unbiasedness criterion
sparse system identification
Online Access:https://ieeexplore.ieee.org/document/8283522/

Internet

https://ieeexplore.ieee.org/document/8283522/

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