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- W102431061 abstract "In this paper consequences of low bit representation and pling on parameter identification are considered. Low bit representation that can be motivated by speed and cost constraints on A/D converters, induces bounded measurement errors on data. Such errors appear to be uniformly distributed so that parameter identification with algorithms developed in the bounded noise context is effective. Possible additional gaussian measurement errors does not affect the performances especially when their variance is low compared with the truncation error. If oversampling is possible, preprocessing of oversampled data with central algorithms is effective and leads to final identification results similar to those that could be achieved with higher bit representation. The different features are illustrated with a simulation study on a MA system." @default.
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- W102431061 date "1996-06-01" @default.
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- W102431061 title "Estimation Under Low Bit Representation" @default.
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- W102431061 doi "https://doi.org/10.1016/s1474-6670(17)58307-x" @default.
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