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Optimization of Number Representations

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Handbook of Signal Processing Systems

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Abstract

In this section, automatic scaling and word-length optimization procedures for efficient implementation of signal processing systems are explained. For this purpose, a fixed-point data format that contains both integer and fractional parts is introduced, and used for systematic and incremental conversion of floating-point algorithms into fixed-point or integer versions. A simulation based range estimation method is explained, and applied to automatic scaling of C language based digital signal processing programs. A fixed-point optimization method is also discussed, and optimization examples including a recursive filter and an adaptive filter are shown.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Seoul National University, Gwanak-gu, Seoul, Republic of Korea

    Wonyong Sung

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  1. Wonyong Sung
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Correspondence to Wonyong Sung .

Editor information

Editors and Affiliations

  1. Department of ECE and UMIACS, University of Maryland, College Park, MD, USA

    Shuvra S. Bhattacharyya

  2. Leiden Embedded Research Center, Leiden University Leiden Institute Advanced Computer Science, Leiden, The Netherlands

    Ed F. Deprettere

  3. RWTH Aachen University Software for Systems on Silicon, Aachen, Germany

    Rainer Leupers

  4. Department of Pervasive Computing, Tampere University of Technology, Tampere, Finland

    Jarmo Takala

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Sung, W. (2019). Optimization of Number Representations. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-91734-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-91734-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91733-7

  • Online ISBN: 978-3-319-91734-4

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