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Quantizer Optimization:Application of Passivity in Telecommunications

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Model Identification and Adaptive Control

Abstract

Passivity theory is used to examine the stability of a generalized decision feedback structure which incorporates a general memoryless non-linearity. This non-linearity is considered in lieu of the nearest neighbor quantizer conventionally used for generating data estimates that are fed back. By associating error propagation recovery in a finite time with stability, we determine an optimal class of memoryless non-linearities. This class includes the saturation characteristic. Among constrained quantization rules, we also determine the optimal size of a quantizer deadband region - a problem that has been previously been raised in the literature on erasures in decision feedback equalization. These new general structures are shown theoretically to have superior error propagation suppression characteristics to the conventional decision feedback equalizer. The theoretical results are corroborated by a set of simulations.

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Author information

Authors and Affiliations

  1. Telecommunications Engineering, RSISE, The Australian National University, Canberra, ACT 0200, Australia

    Rodney A. Kennedy

  2. Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA

    Zhi Ding

  3. Asia Pacific Institute of Information Technology, Karachi, Pakistan

    Shazia Hasnie

Authors
  1. Rodney A. Kennedy
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  2. Zhi Ding
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  3. Shazia Hasnie
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Newcastle, Callaghan, 2308, NSW, Australia

    Graham Goodwin BSc, BE PhD, FIEEE, Hon FIE Aust., FTS, FAA

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© 2001 Springer-Verlag London Limited

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Kennedy, R.A., Ding, Z., Hasnie, S. (2001). Quantizer Optimization:Application of Passivity in Telecommunications. In: Goodwin, G. (eds) Model Identification and Adaptive Control. Springer, London. https://doi.org/10.1007/978-1-4471-0711-8_8

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  • DOI: https://doi.org/10.1007/978-1-4471-0711-8_8

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1185-6

  • Online ISBN: 978-1-4471-0711-8

  • eBook Packages: Springer Book Archive

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