Signal Useful Information Recovery by Overlapping Supports of Time-Frequency Representations

被引：0

作者：

Saulig, Nicoletta ^{[1
]}

Milovanovic, Milos ^{[2
]}

Milicic, Sinisa ^{[3
]}

Lerga, Jonatan ^{[4
]}

机构：

[1] Juraj Dobrila University of Pula, Faculty of Engineering, Pula,52100, Croatia

[2] Mathematical Institute, The Serbian Academy of Sciences and Arts, Belgrade,11000, Serbia

[3] Juraj Dobrila University of Pula, Faculty of Informatics, Pula,52100, Croatia

[4] University of Rijeka, Faculty of Engineering, Rijeka,51000, Croatia

来源：

IEEE Transactions on Signal Processing | 2022年 / 70卷

关键词：

Entropy - Frequency modulation - Information use - Inverse problems - Signal reconstruction;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper presents a novel method for automatic extraction of useful information from time-frequency distributions of noisy signals. Signals' features are examined through the combined analysis of their time-frequency energy distributions and inverse complexity maps. The inverse complexity approach gives a new entropy-based insight into the signal structure. These two approaches result in mostly disjoint time-frequency supports, overlapping only in the proximity of the signal components. Locations of the signal components (i.e., useful information) are thus identified by low complexity and high amplitude occurring together in the time-frequency plane. Compared to existing methods using only the time-frequency energy distribution, useful information extraction by the proposed method exhibits a significantly reduced error rate. © 2022 IEEE.

引用

页码：5504 / 5517