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

The author discusses this for both 1-D (such as required, for example, for the spectrum analysis of audio signals) and m‑D (such as required, for example, for the compression of noisy 2-D images or the watermarking of 3-D video signals) cases, but requiring few computing resources (i.e. low arithmetic/memory/power requirements, etc.). This is particularly relevant for those application areas, such as mobile communications, where the available silicon resources (as well as the battery-life) are expected to be limited. The aim of this monograph, where silicon‑based computing technology and a resource‑constrained environment is assumed and the data is real-valued in nature, has thus been to seek solutions that best match the actual problem needing to be solved.