08 اردیبهشت 1403
سعيد طهماسبي

سعید طهماسبی

مرتبه علمی: دانشیار
نشانی: دانشکده مهندسی سیستم های هوشمند و علوم داده - گروه آمار
تحصیلات: دکترای تخصصی / آمار ریاضی
تلفن: 077-31223329
دانشکده: دانشکده مهندسی سیستم های هوشمند و علوم داده

مشخصات پژوهش

عنوان COMPRESSIVE SENSING USING EXTROPY MEASURES OF RANKED SET SAMPLING
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Compressive sensing, cumulative extropy, maximum ranked set sampling, record ranked set sampling, stochastic ordering.
مجله Mathematica Slovaca
شناسه DOI https://doi.org/10.1515/ms-2023-0021
پژوهشگران سعید طهماسبی (نفر اول) ، محمد رضا کاظمی (نفر دوم) ، احمد کشاورز (نفر سوم) ، علی اکبر جعفری (نفر چهارم) ، Francesco Buono (نفر پنجم)

چکیده

The aim of this paper is to consider the extropy measure of uncertainty proposed by Lad, Sanfilippo and Agro for the problem of compressive sensing. For this purpose, two sampling designs, i.e., simple random sampling (SRS) and a modified version of ranked set sampling, known as maximum ranked set sampling procedure with unequal samples (MRSSU), are utilized and some uncertainty measures such as extropy, cumulative extropy and residual extropy are obtained and compared for these sampling designs. Also, some results of extropy in record ranked set sampling data are developed. Then a study on comparing the behavior of estimators of cumulative extropy in MRSSU and SRS using simulation method is obtained. As an example, two sampling methods MRSSU and SRS are utilized for compressive sensing technique and their performances are compared via signal to noise ratio (SNR), correlation coefficient of reconstructed and the original signal and cumulative extropy measure of uncertainty. The results show that the values of SNR and correlation coefficient for MRSSU are higher than those of SRS. Furthermore, it is shown that MRSSU scheme can efficiently reduce the uncertainty measure of cumulative extropy.