Effect of Finite Wordlength on the Performance of an Adaptive Network

Wael Bazzi; Amir Rastegarnia; Azam Khalili

Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers

Research Article

Effect of Finite Wordlength on the Performance of an Adaptive Network

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@INPROCEEDINGS{10.1007/978-3-319-11629-7_17,
    author={Wael Bazzi and Amir Rastegarnia and Azam Khalili},
    title={Effect of Finite Wordlength on the Performance of an Adaptive Network},
    proceedings={Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers},
    proceedings_a={SPIT},
    year={2014},
    month={11},
    keywords={adaptive networks distributed estimation least mean-square (LMS) quantization},
    doi={10.1007/978-3-319-11629-7_17}
}

Wael Bazzi
Amir Rastegarnia
Azam Khalili
Year: 2014
Effect of Finite Wordlength on the Performance of an Adaptive Network
SPIT
Springer
DOI: 10.1007/978-3-319-11629-7_17

Wael Bazzi¹^,*, Amir Rastegarnia²^,*, Azam Khalili²^,*

1: American University in Dubai
2: Malayer University

*Contact email: wbazzi@aud.edu, a_rastegar@ieee.org, a.khalili@ieee.org

Abstract

In this paper we consider the performance of incremental least mean square (ILMS) adaptive network when it is implemented in finite-precision arithmetic. We show that unlike the infinite-precision case, the steady-state curve, described in terms of mean square deviation (MSD) is not always a monotonic increasing function of step-size parameter. More precisely, when the quantization level is small, reducing the step-size may increase the steady-state MSD.

Keywords: adaptive networks distributed estimation least mean-square (LMS) quantization

Published: 2014-11-28

: http://dx.doi.org/10.1007/978-3-319-11629-7_17