dc.contributor.authorVun, Chan Hua
dc.contributor.authorZhang, Wei
dc.contributor.authorPremkumar, Annamalai Benjamin
dc.date.accessioned2013-12-10T01:19:18Z
dc.date.available2013-12-10T01:19:18Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.citationVun, C. H., Premkumar, A. B., & Zhang, W. (2013). A new RNS based DA approach for inner product computation. IEEE transactions on circuits and systems I : Regular papers, 60(8), 2139-2152.en_US
dc.identifier.urihttp://hdl.handle.net/10220/18182
dc.description.abstractThis paper presents a novel method to perform inner product computation based on the distributed arithmetic principles. The input data are represented in the residue domain and are encoded using the thermometer code format while the output data are encoded in the one-hot code format. Compared to the conventional distributed arithmetic based system using binary coded format to represent the residues, the proposed system using the thermometer code encoded residues provides a simple means to perform the modular inner products computation due to the absence of the 2 modulo operation encountered in conventional binary code encoded system. In addition, the modulo adder used in the proposed system can be implemented using simple shifter based circuit utilizing one-hot code format. As there is no carry propagation involved in the addition using one-hot code, while the modulo operation can be performed automatically during the addition process, the operating speed of the one-hot code based modulo adder is much superior compared to the conventional binary code based modulo adder. As inner product is used extensively in FIR filter design, SPICE simulation results for an FIR filter implemented using the proposed system is also presented to demonstrate the validity of the proposed scheme.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesIEEE transactions on circuits and systems I : Regular papersen_US
dc.rights© 2013 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. Published version of this article is available at http://dx.doi.org/10.1109/TCSI.2013.2239164.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleA new RNS based DA approach for inner product computationen_US
dc.typeJournal Article
dc.identifier.doihttp://dx.doi.org/10.1109/TCSI.2013.2239164
dc.description.versionAccepted versionen_US


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