The Regularized Fast Hartley Transform: Low-Complexity Parallel Computation of the FHT in One and Multiple Dimensions

This book discusses how to formulate a key signal/image processing algorithm, the fast Hartley transform (FHT), to facilitate computationally-efficient solutions for 1-D and m-D cases, with low arithmetic/memory/power requirements, particularly relevant for mobile communications.

Format: Paperback / softback
Length: 320 pages
Publication date: 04 September 2022
Publisher: Springer Nature Switzerland AG

This book delves into the formulation of a crucial signal processing algorithm, known as the fast Hartley transform (FHT), or its real-data counterpart, the fast Fourier transform (FFT). Its primary objective is to provide computationally efficient solutions for diverse applications, spanning both 1-D and m-D scenarios. By leveraging the fast Hartley transform, the author aims to achieve low arithmetic/memory/power requirements, making it particularly relevant in resource-constrained environments such as mobile communications.

The author discusses the application of the fast Hartley transform in various fields, including spectrum analysis of audio signals and compression of noisy 2-D images or watermarking of 3-D video signals. The focus is on finding solutions that align optimally with the specific problem at hand, taking into account the assumptions of silicon-based computing technology and a resource-constrained environment where real-valued data is involved.

The monograph aims to bridge the gap between theory and practice, offering practical insights and methodologies for implementing the fast Hartley transform and its real-data counterpart effectively. It serves as a valuable resource for researchers, engineers, and practitioners seeking to optimize signal processing algorithms in resource-constrained environments.

Weight: 522g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030682477
Edition number: 2nd ed. 2022