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High-throughput memory-based architecture for DHT using a new convolutional formulation

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High-throughput memory-based architecture for DHT using a new convolutional formulation

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Title: High-throughput memory-based architecture for DHT using a new convolutional formulation
Author: Meher, Pramod Kumar; Patra, Jagdish Chandra; Swamy, M. N. S.
Copyright year: 2007
Abstract: A new formulation is presented for the computation of an -point discrete Hartley transform (DHT) from two pairs of [(N/2-1)/2]-point cyclic convolutions, and further used to obtain modular structures consisting of simple and regular memory-based systolic arrays for concurrent pipelined realization of the DHT. The proposed structures for direct-memory-based implementation is found to involve nearly the same hardware complexity as those of the existing structures, but offers two to four times more throughput and two to four times less latency compared with others. The distributed-arithmetic (DA)-based implementation is also found to offer very less memory-complexity and considerably low area-delay complexity compared with the existing DA-based structures.
Subject: DRNTU::Engineering::Computer science and engineering::Computer systems organization::Processor architectures.
Type: Journal Article
Series/ Journal Title: IEEE transactions on circuits and Systems II: express briefs
School: School of Computer Engineering
Rights: © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [DOI: http://dx.doi.org/10.1109/TCSII.2007.894407].
Version: Accepted version

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