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Split-radix FFT algorithm
About: Split-radix FFT algorithm is a research topic. Over the lifetime, 1845 publications have been published within this topic receiving 41398 citations.
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TL;DR: A new method for calculating effective atomic radii within the generalized Born (GB) model of implicit solvation is proposed, for use in computer simulations of bio-molecules, and is able to reach the accuracy of other existing GB implementations, while offering much lower computational cost.
11 citations
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TL;DR: The Hartley Transform not only decreases the computer time of the WDF but also simplifies the convolution of two WDFs, which is used here to simulate a blurred image and its restoration.
11 citations
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TL;DR: The novel aspects of the specific FFT method described include: a bit-wise reversal re-grouping operation of the conventional FFT is replaced by the use of lossless image rotation and scaling and the usual arithmetic operations of complex multiplication are replaced with integer addition.
Abstract: The Fourier transform is one of the most important transformations in image processing. A major component of this influence comes from the ability to implement it efficiently on a digital computer. This paper describes a new methodology to perform a fast Fourier transform (FFT). This methodology emerges from considerations of the natural physical constraints imposed by image capture devices (camera/eye). The novel aspects of the specific FFT method described include: 1) a bit-wise reversal re-grouping operation of the conventional FFT is replaced by the use of lossless image rotation and scaling and 2) the usual arithmetic operations of complex multiplication are replaced with integer addition. The significance of the FFT presented in this paper is introduced by extending a discrete and finite image algebra, named Spiral Honeycomb Image Algebra (SHIA), to a continuous version, named SHIAC
11 citations
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TL;DR: For real-time applications that require recalculating the DFT at each sample or over only a subset of the N center frequencies, the FFT is far from optimal.
Abstract: The discrete Fourier transform (DFT) is the standard tool for spectral analysis in digital signal processing, typically computed using the fast Fourier transform (FFT). However, for real-time applications that require recalculating the DFT at each sample or over only a subset of the N center frequencies of the DFT, the FFT is far from optimal.
11 citations
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TL;DR: In this paper, a fixed-point error analysis has been carried out for the fast Hartley transform (FHT) and the results are compared with the FFT error-analysis results.
11 citations