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
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.
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