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Journal ArticleDOI

Discrete Hartley transform

Ronald N. Bracewell
- 01 Dec 1983 - 
- Vol. 73, Iss: 12, pp 1832-1835
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TLDR
The discrete Hartley transform (DHT) resembles the discrete Fourier transform (DFT) but is free from two characteristics of the DFT that are sometimes computationally undesirable and promises to speed up Fourier-transform calculations.
Abstract
The discrete Hartley transform (DHT) resembles the discrete Fourier transform (DFT) but is free from two characteristics of the DFT that are sometimes computationally undesirable. The inverse DHT is identical with the direct transform, and so it is not necessary to keep track of the +i and −i versions as with the DFT. Also, the DHT has real rather than complex values and thus does not require provision for complex arithmetic or separately managed storage for real and imaginary parts. Nevertheless, the DFT is directly obtainable from the DHT by a simple additive operation. In most image-processing applications the convolution of two data sequences f1 and f2 is given by DHT of [(DHT of f1) × (DHT of f2)], which is a rather simpler algorithm than the DFT permits, especially if images are. to be manipulated in two dimensions. It permits faster computing. Since the speed of the fast Fourier transform depends on the number of multiplications, and since one complex multiplication equals four real multiplications, a fast Hartley transform also promises to speed up Fourier-transform calculations. The name discrete Hartley transform is proposed because the DHT bears the same relation to an integral transform described by Hartley [ HartleyR. V. L., Proc. IRE30, 144 ( 1942)] as the DFT bears to the Fourier transform.

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Citations
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Proceedings ArticleDOI

A computation engine for the FFT/FCT/FHT using AT&T DSP32

TL;DR: The AT&T DSP32 chip, a programmable digital signal processor with a 32-b floating-point arithmetic unit and a 16-MHz operation rate, can be used for computing the discrete Fourier, cosine, and Hartley transforms.
Proceedings ArticleDOI

Representation and approximation of time-varying systems via real-valued discrete Gabor transforms

TL;DR: Compared with the existing method based on the traditional complex-valued discrete Gabor transform, the proposed method is faster and can more easily be implemented in software or hardware as well as leads to a more compact representation.
Journal ArticleDOI

A discrete Hartley transform based on Simpson's rule

TL;DR: In this article, a discrete Hartley transform is proposed as a real transform with a convolution property and is an alternative to the discrete Fourier transform, which is an integral transformation that maps a real value function into a real valued frequency function via the Hartley kernel.

Hartley Transform: Basic Theory And Applications In Oceanographic Time Series Analysis

G Rodríguez
TL;DR: The Hartley transform is used to estimate the spectral density of ocean surface waves and coastal current time series and is presented as an efficient tool for data analysis in physical oceanography.
Book ChapterDOI

State of the Art on Transmission Techniques

TL;DR: This chapter provides an overview of the state of the art of optical fibre transmission techniques, facilitating the use of coherent detection and the mitigation of nonlinear effects, as well as allowing the application of advanced transmission techniques such as orthogonal frequency division multiplexing (OFDM).
References
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Book

The Fourier Transform and Its Applications

TL;DR: In this paper, the authors provide a broad overview of Fourier Transform and its relation with the FFT and the Hartley Transform, as well as the Laplace Transform and the Laplacian Transform.
Journal ArticleDOI

A More Symmetrical Fourier Analysis Applied to Transmission Problems

TL;DR: In this article, the Fourier identity is expressed in a more symmetrical form which leads to certain analogies between the function of the original variable and its transform, and it permits a function of time to be analyzed into two independent sets of sinusoidal components, one of which is represented in terms of positive frequencies, and the other of negative.
Journal ArticleDOI

Harmonic analysis with a real frequency function—I. aperiodic case

TL;DR: An integral transform which converts a real spatial (or temporal) function into a real frequency function is introduced in this paper, and the properties of this transform are investigated, and it is concluded that this transform is parallel to the Fourier transform and may be applied to all fields in which the FFT has been successfully applied.