The Fast Hartley Transform

Abstract

The purpose of this paper is to report the results of testing the Fast Hartley Transform (FHT) and comparing it with the Fast Fourier Transform (FFT). All the definitions and equations in this paper are quoted and cited from the series of references. The author of this report developed a Fortran program which computes the Hartley transform. He tested the program with a generalized electromagnetic pulse waveform and verified the results with the known value. Fourier analysis is an essential tool to obtain frequency domain information from transient time domain signals. The FFT is a popular tool to process many of today's audio and electromagnetic signals. System frequency response, digital filtering of signals, and signal power spectrum are the most practical applications of the FFT. However, the Fourier integral transform of the FFT requires the computer resources appropriate to the complex arithmetic operations. On the other hand, the FHT can accomplish the same results faster and requires fewer computer resources. The FHT is twice as fast as the FFT, uses only half the computer resources, and so could be more useful than the FFT in typical applications such as spectral analysis, signal processing, and convolution. This paper presents a Fortran computer program for the FHT algorithm along with a brief description and compares the results and performance of the FHT and the FFT algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1990
Accession Number
ADA230370

Entities

People

  • Mark H. Mar

Organizations

  • Harry Diamond Laboratories

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programs
  • Computers
  • Convolution
  • Data Sets
  • Electrical Engineering
  • Engineering
  • Fast Fourier Transforms
  • Fourier Analysis
  • Frequency
  • Frequency Domain
  • Integral Transforms
  • Integrals
  • Power Spectra
  • Signal Processing
  • Time Domain
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Image Processing and Computer Vision.