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Jasifa Fayaz

Publications and source records attributed to Jasifa Fayaz.

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The Quaternion Boostlet Transform: Definition, Properties and Uncertainty Principles

In this article, we introduce the notion of Quaternion Boostlet Transform (QBT), a hypercomplex framework designed to unify the analysis of multi-component wavefields by merging the algebraic richness of quaternions with the relativistic, hyperbolic geometry of the boostlet system. By treating coupled physical phenomena such as acoustic pressure with particle velocity or orthogonally polarized elastic displacements as single quaternion-valued entities, the QBT preserves intrinsic geometric correlations that are typically lost in component-wise processing. We also establish a rigorous mathematical foundation for the transform, including the admissibility condition, a convolution-based representation, a Plancherel theorem for energy conservation, and an explicit inversion formula ensuring perfect signal reconstruction. Furthermore, the work derives a comprehensive set of uncertainty principles namely Heisenberg, logarithmic, and Pitt's inequalities that define the precise localization constraints of QBT coefficients in the augmented phase space. The theoretical development is substantiated with illustrative examples, wherein the QBT is applied to a quaternion-valued plane wave featuring coupled pressure-velocity components and to a Gaussian-modulated circularly polarized elastic wave packet. These examples demonstrate how the transform naturally encodes wavefront orientation and polarization state through quaternion phase, offering a physically coherent and sparse dictionary for vector-valued wavefield analysis in acoustics and seismology.

math.FA

Continuous Boostlet Transform and Associated Uncertainty Principles

The Continuous Boostlet Transform (CBT) is introduced as a powerful tool for analyzing spatiotemporal signals, particularly acoustic wavefields. Overcoming the limitations of classical wavelets, the CBT leverages the Poincar\'e group and isotropic dilations to capture sparse features of natural acoustic fields. This paper presents the mathematical framework of the CBT, including its definition, fundamental properties, and associated uncertainty principles, such as Heisenberg's, logarithmic, Pitt's, and Nazarov's inequalities. These results illuminate the trade-offs between time and frequency localization in the boostlet domain. Practical examples with constant and exponential functions highlight the CBT's adaptability. With applications in radar, communications, audio processing, and seismic analysis, the CBT offers flexible time-frequency resolution, making it ideal for non-stationary and transient signals, and a valuable tool for modern signal processing.

eess.SP