Asymptotic Properties of a One-bit Estimator of Parametric Signals Article Swipe

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Paolo Carbone , Alessio De Angelis , Antonio Moschitta , Francesco Santoni ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.36227/techrxiv.22651516.v1

This paper considers an estimator of the parameters in a linear-in-the-parameter signal, based on its binary quantization. It shows an analysis of the systematic errors for growing lengths of the data set. It also shows how to express the cost function, when the minimum is reached. Zero-mean additive noise is assumed in the model, having independent outcomes. Furthermore, a method is introduced to validate the estimation process. Monte Carlo results validate the proposed analyses.

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Monte Carlo Method

Mathematics

Quantization (Signal Processing)

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Estimator Monte Carlo method Mathematics Parametric statistics Quantization (signal processing) Binary number Algorithm Applied mathematics Function (biology) Statistics Computer science Arithmetic Biology Evolutionary biology

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Type: preprint
Language: en
Landing Page: https://doi.org/10.36227/techrxiv.22651516.v1
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DOI: https://doi.org/10.36227/techrxiv.22651516.v1

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Title: Asymptotic Properties of a One-bit Estimator of Parametric Signals

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-04-25

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Authors: Paolo Carbone, Alessio De Angelis, Antonio Moschitta, Francesco Santoni

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Landing page: https://doi.org/10.36227/techrxiv.22651516.v1

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Concepts: Estimator, Monte Carlo method, Mathematics, Parametric statistics, Quantization (signal processing), Binary number, Algorithm, Applied mathematics, Function (biology), Statistics, Computer science, Arithmetic, Biology, Evolutionary biology

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