Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Michaeli Linus"'
Publikováno v:
Measurement Science Review, Vol 19, Iss 1, Pp 35-42 (2019)
Compressive sensing is a processing approach aiming to reduce the data stream from the observed object with the inherent sparsity using the optimal signal models. The compression of the sparse input signal in time or in the transform domain is perfor
Externí odkaz:
https://doaj.org/article/5fd484eeee174bcfb33523f65dd51193
Publikováno v:
Measurement Science Review, Vol 18, Iss 5, Pp 175-182 (2018)
This paper presents a way of acquiring a sparse signal by taking only a limited number of samples; sampling and compression are performed in one step by the analog to information conversion. The signal is recovered with minimal information loss from
Externí odkaz:
https://doaj.org/article/7132b5cd0707451b81056e16ef031ec8
Autor:
Michaeli Linus, Šaliga Ján
Publikováno v:
Measurement Science Review, Vol 14, Iss 2, Pp 62-77 (2014)
Error models of the Analog to Digital Converters describe metrological properties of the signal conversion from analog to digital domain in a concise form using few dominant error parameters. Knowledge of the error models allows the end user to provi
Externí odkaz:
https://doaj.org/article/d0bd623f482545c09d947add40f568bb
Publikováno v:
In Measurement October 2021 183
Publikováno v:
In Measurement December 2013 46(10):4362-4368
Publikováno v:
In Measurement 2012 45(2):164-169
Publikováno v:
In Measurement 2010 43(8):1061-1068
Publikováno v:
In Measurement 2008 41(2):198-204
Publikováno v:
In Measurement 2008 41(2):192-197
Publikováno v:
In Measurement 2007 40(5):491-499