{"title":"Discrete biquaternion linear canonical transform","authors":"Owais Ahmad, Aijaz Ahmad Dar","doi":"10.1016/j.cam.2025.117010","DOIUrl":null,"url":null,"abstract":"<div><div>The landscape of signal processing has witnessed significant advancements over the years, driven by the need for efficient and accurate techniques to analyze and manipulate complex data. While traditional Fourier-based methods have been instrumental, they often struggle to capture the intricate nuances of signals that exhibit non-linearity, non-stationarity, or dual characteristics. To address these limitations, a novel approach namely the Discrete Biquaternion Linear Canonical Transform (DBiQLCT) is introduced in this paper. Because of the inherent non-commutativity of biquaternion algebra multiplication, the Discrete Biquaternion Linear Canonical Transform (DBiQLCT) has three unique forms: left-sided DBiQLCT, right-sided DBiQLCT, and two-sided DBiQLCT. We first introduce a notion of DBiQLCT and subsequently investigate the connections between these transformations. Following that, we investigate the two-sided discrete biquaternion linear canonical transform (TDBiQLCT), revealing important fundamental features such as linearity, time shift, conjugate, and modulation. We also establish the Plancherel and convolution theorems associated with the two-sided DBiQLCT. Furthermore, applications of the proposed transform are discussed at the end.</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"474 ","pages":"Article 117010"},"PeriodicalIF":2.6000,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377042725005242","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
The landscape of signal processing has witnessed significant advancements over the years, driven by the need for efficient and accurate techniques to analyze and manipulate complex data. While traditional Fourier-based methods have been instrumental, they often struggle to capture the intricate nuances of signals that exhibit non-linearity, non-stationarity, or dual characteristics. To address these limitations, a novel approach namely the Discrete Biquaternion Linear Canonical Transform (DBiQLCT) is introduced in this paper. Because of the inherent non-commutativity of biquaternion algebra multiplication, the Discrete Biquaternion Linear Canonical Transform (DBiQLCT) has three unique forms: left-sided DBiQLCT, right-sided DBiQLCT, and two-sided DBiQLCT. We first introduce a notion of DBiQLCT and subsequently investigate the connections between these transformations. Following that, we investigate the two-sided discrete biquaternion linear canonical transform (TDBiQLCT), revealing important fundamental features such as linearity, time shift, conjugate, and modulation. We also establish the Plancherel and convolution theorems associated with the two-sided DBiQLCT. Furthermore, applications of the proposed transform are discussed at the end.
期刊介绍:
The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest.
The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.