Residue Number Systems | Algorithms and Architectures

P. V. Ananda Mohan

ISBN 10: 1402070314 / ISBN 13: 9781402070310

Published by Springer, 2002

About this Item

Residue Number Systems | Algorithms and Architectures | P. V. Ananda Mohan | Buch | xiii | Englisch | 2002 | Springer | EAN 9781402070310 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 102592182

Bibliographic Details

• Title: Residue Number Systems | Algorithms and Architectures
• Publisher: Springer
• Publication Date: 2002
• Language: English
• ISBN 10: 1402070314
• ISBN 13: 9781402070310
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 20D millimeters 241 millimeters width by 160 millimeters height by 20 millimeters depth
• Weight: 573 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

There has been continuing interest in the improvement of the speed of Digital Signal processing. The use of Residue Number Systems for the design of DSP systems has been extensively researched in literature. Szabo and Tanaka have popularized this approach through their book published in 1967. Subsequently, Jenkins and Leon have rekindled the interest of researchers in this area in 1978, from which time there have been several efforts to use RNS in practical system implementation. An IEEE Press book has been published in 1986 which was a collection of Papers. It is very interesting to note that in the recent past since 1988, the research activity has received a new thrust with emphasis on VLSI design using non­ ROM based designs as well as ROM based designs as evidenced by the increased publications in this area. The main advantage in using RNS is that several small word-length Processors are used to perform operations such as addition, multiplication and accumulation, subtraction, thus needing less instruction execution time than that needed in conventional 16 bitl32 bit DSPs. However, the disadvantages of RNS have b. een the difficulty of detection of overflow, sign detection, comparison of two numbers, scaling, and division by arbitrary number, RNS to Binary conversion and Binary to RNS conversion. These operations, unfortunately, are computationally intensive and are time consuming.