Complex-Valued Signals: a Tutorial for Non-Circular Data Processing and Analysis

This work explores the versatility of complex-valued signals present in data representation in diverse applications. Integrating complex values into signals and processing structures proves powerful in system modeling, demonstrating effectiveness in many scenarios. The inherent mathematical efficiency of complex numbers enhances both elegance and practical utility, simplifying calculations and expanding capabilities. However, the use of complex notation introduces considerations related to the intrinsic geometry of the data. This tutorial unravels the theoretical foundations and practical applications in adaptive filtering of complex-valued signals, emphasizing the importance of understanding the displayed profiles of the studied signals and data. Using complex augmented notation and widely linear processing, superior performance is attainable in specific cases, providing valuable information to readers interested in signal processing.

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Publication Details

Journal
Journal of Communication and Information Systems
Published
2025-10-07
DOI
https://doi.org/10.14209/jcis.2025.07
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
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article

Complex-Valued Signals: a Tutorial for Non-Circular Data Processing and Analysis

João Mota, Charles C. Cavalcante, Rafale Bluhm
Journal of Communication and Information Systems
Neural Networks and Applications
article

Complex-Valued Signals: a Tutorial for Non-Circular Data Processing and Analysis

João Mota, Charles C. Cavalcante, Rafale Bluhm
article en

Abstract

This work explores the versatility of complex-valued signals present in data representation in diverse applications. Integrating complex values into signals and processing structures proves powerful in system modeling, demonstrating effectiveness in many scenarios. The inherent mathematical efficiency of complex numbers enhances both elegance and practical utility, simplifying calculations and expanding capabilities. However, the use of complex notation introduces considerations related to the intrinsic geometry of the data. This tutorial unravels the theoretical foundations and practical applications in adaptive filtering of complex-valued signals, emphasizing the importance of understanding the displayed profiles of the studied signals and data. Using complex augmented notation and widely linear processing, superior performance is attainable in specific cases, providing valuable information to readers interested in signal processing.

Journal of Communication and Information SystemsVol. 40(2025)
Universidade Federal do Ceará (BR), United Food and Commercial Workers (US)
Openalex Percentile: Top 85%
Neural Networks and Applications
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