Statistical Properties of SNR for Compressed Measurements

المؤلفون المشاركون

Gao, Yulong
Chen, Yanping
Su, Linxiao

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-6، 6ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2016-09-25

دولة النشر

مصر

عدد الصفحات

6

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Some basic statistical properties of the compressed measurements are investigated.

It is well known that the statistical properties are a foundation for analyzing the performance of signal detection and the applications of compressed sensing in communication signal processing.

Firstly, we discuss the statistical properties of the compressed signal, the compressed noise, and their corresponding energy.

And then, the statistical characteristics of SNR of the compressed measurements are calculated, including the mean and the variance.

Finally, probability density function and cumulative distribution function of SNR are derived for the cases of the Gamma distribution and the Gaussian distribution.

Numerical simulation results demonstrate the correctness of the theoretical analysis.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Gao, Yulong& Chen, Yanping& Su, Linxiao. 2016. Statistical Properties of SNR for Compressed Measurements. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1112018

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Gao, Yulong…[et al.]. Statistical Properties of SNR for Compressed Measurements. Mathematical Problems in Engineering No. 2016 (2016), pp.1-6.
https://search.emarefa.net/detail/BIM-1112018

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Gao, Yulong& Chen, Yanping& Su, Linxiao. Statistical Properties of SNR for Compressed Measurements. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1112018

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1112018