Topic
Hartley transform
About: Hartley transform is a research topic. Over the lifetime, 2709 publications have been published within this topic receiving 79944 citations.
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TL;DR: It is shown that these basefield transforms can be viewed as "projections" of the discrete Fourier transform (DFT) and that they exist for all lengths N for which the DFT is defined.
Abstract: A general framework is presented for constructing transforms in the field of the input which have a convolution-like property. The construction is carried out over finite fields, but is shown to be valid over the real and complex fields as well. It is shown that these basefield transforms can be viewed as "projections" of the discrete Fourier transform (DFT) and that they exist for all lengths N for which the DFT is defined. The convolution property of the basefield transforms is derived and a condition for such transforms to have the self-inverse property is given. Also, fast algorithms for these basefield transforms are developed, showing gains when compared to computations using the FFT. Application of the methodology to Hartley transforms over R leads to a simple derivation of fast algorithms for computing real Hartley transforms. >
19 citations
TL;DR: In this article, a least squares IIR (infinite impulse response) algorithm, in the transformed domains, which fits each of the retained subsets of the complex transform components accurately, is presented.
Abstract: The mixed transform representation of time-varying signals uses partial sets of basis functions from the discrete Fourier transform (DFT) and the Walsh-Hadamard transform. The location, magnitude, and phase of the transform components have to be specified for proper signal reconstruction. A least-squares IIR (infinite impulse response) algorithm, in the transformed domains, which fits each of the retained subsets of the complex transform components accurately, is presented. The IIR function, while characterized by real coefficients about twice the number of the retained complex transform components, carries enough location, magnitude, and phase information for accurate signal reconstruction. To illustrate the technique's accuracy and efficiency, its application to model the DFT part of a voice speech segment is given. >
19 citations
TL;DR: This algorithm offers substantial reductions in the numbers of multiplications, additions, data transfers, and twiddle factor evaluations or accesses to the look-up table, without a significant increase in the structural complexity compared to that of the existing 3-D vector radix FHT algorithm.
Abstract: In this paper, we propose a three-dimensional (3-D) split vector-radix fast Hartley transform (FHT) algorithm. The main idea behind the proposed algorithm is that the radix-2/4 approach is introduced in the decomposition of the 3-D discrete Hartley transform by using an appropriate index mapping and the Kronecker product. This provides an algorithm based on a mixture of radix-(2times2times2) and radix-(4times4times4) index maps and has a butterfly that is characterized by simple closed-form expressions. This algorithm offers substantial reductions in the numbers of multiplications, additions, data transfers, and twiddle factor evaluations or accesses to the look-up table, without a significant increase in the structural complexity compared to that of the existing 3-D vector radix FHT algorithm
19 citations
01 Jan 2004
TL;DR: In this article, a generalization of the Radon transform to the infinite dimensional setting, using Gauss measure instead of Lebesgue measure, is presented. But this generalization is restricted to a single hyperplane in an infinite dimensional Hilbert space.
Abstract: Gaussian measure is constructed for any given hyperplane in an infinite dimensional Hilbert space, and this is used to define a generalization of the Radon transform to the infinite dimensional setting, using Gauss measure instead of Lebesgue measure. An inversion formula is obtained and a support theorem proved.
19 citations
TL;DR: In this paper, a Fourier transform based algorithm for the reconstruction of functions from their nonstandard sampled Radon transform is proposed, which incorporates recently developed fast Fourier transforms for nonequispaced data.
Abstract: In this paper, we suggest a new Fourier transform based algorithm forthe reconstruction of functions from their nonstandard sampled Radon transform. The algorithm incorporates recently developed fast Fourier transforms for nonequispaced data. We estimate the-corresponding aliasing error in dependence on the sampling geometry of the Radon transform and confirm our theoretical results by numerical examples.
19 citations