Further Discussion on Modeling of Measuring Process via Sampling of Signals
In this paper, we continue a topic of modeling measuring processes by perceiving them as a kind of signal sampling. And, in this respect, note that an ideal model was developed in a previous work. Whereas here, we present its nonideal version. This extended model takes into account an effect, which...
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2020-09-01
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| Series: | International Journal of Electronics and Telecommunications |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/117101/PDF/70_2407_Borys_skl_new.pdf |
| _version_ | 1818489211911667712 |
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| author | Andrzej Borys |
| author_facet | Andrzej Borys |
| author_sort | Andrzej Borys |
| collection | DOAJ |
| description | In this paper, we continue a topic of modeling measuring processes by perceiving them as a kind of signal sampling. And, in this respect, note that an ideal model was developed in a previous work. Whereas here, we present its nonideal version. This extended model takes into account an effect, which is called averaging of a measured signal. And, we show here that it is similar to smearing of signal samples arising in nonideal signal sampling. Furthermore, we demonstrate in this paper that signal averaging and signal smearing mean principally the same, under the conditions given. So, they can be modeled in the same way. A thorough analysis of errors related to the signal averaging in a measuring process is given and illustrated with equivalent schemes of the relationships derived. Furthermore, the results obtained are compared with the corresponding ones that were achieved analyzing amplitude quantization effects of sampled signals used in digital techniques. Also, we show here that modeling of errors related to signal averaging through the so-called quantization noise, assumed to be a uniform distributed random signal, is rather a bad choice. In this paper, an upper bound for the above error is derived. Moreover, conditions for occurrence of hidden aliasing effects in a measured signal are given. |
| first_indexed | 2024-12-10T17:01:22Z |
| format | Article |
| id | doaj.art-50b9e5f91f2f43f48a0f3a9029b383e1 |
| institution | Directory Open Access Journal |
| issn | 2081-8491 2300-1933 |
| language | English |
| last_indexed | 2024-12-10T17:01:22Z |
| publishDate | 2020-09-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | International Journal of Electronics and Telecommunications |
| spelling | doaj.art-50b9e5f91f2f43f48a0f3a9029b383e12022-12-22T01:40:34ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332020-09-01vol. 66No 3507513https://doi.org/10.24425/ijet.2020.134006Further Discussion on Modeling of Measuring Process via Sampling of SignalsAndrzej BorysIn this paper, we continue a topic of modeling measuring processes by perceiving them as a kind of signal sampling. And, in this respect, note that an ideal model was developed in a previous work. Whereas here, we present its nonideal version. This extended model takes into account an effect, which is called averaging of a measured signal. And, we show here that it is similar to smearing of signal samples arising in nonideal signal sampling. Furthermore, we demonstrate in this paper that signal averaging and signal smearing mean principally the same, under the conditions given. So, they can be modeled in the same way. A thorough analysis of errors related to the signal averaging in a measuring process is given and illustrated with equivalent schemes of the relationships derived. Furthermore, the results obtained are compared with the corresponding ones that were achieved analyzing amplitude quantization effects of sampled signals used in digital techniques. Also, we show here that modeling of errors related to signal averaging through the so-called quantization noise, assumed to be a uniform distributed random signal, is rather a bad choice. In this paper, an upper bound for the above error is derived. Moreover, conditions for occurrence of hidden aliasing effects in a measured signal are given.https://journals.pan.pl/Content/117101/PDF/70_2407_Borys_skl_new.pdfmeasuring processsampling of signalssmearing and averaging of signal samples |
| spellingShingle | Andrzej Borys Further Discussion on Modeling of Measuring Process via Sampling of Signals International Journal of Electronics and Telecommunications measuring process sampling of signals smearing and averaging of signal samples |
| title | Further Discussion on Modeling of Measuring Process via Sampling of Signals |
| title_full | Further Discussion on Modeling of Measuring Process via Sampling of Signals |
| title_fullStr | Further Discussion on Modeling of Measuring Process via Sampling of Signals |
| title_full_unstemmed | Further Discussion on Modeling of Measuring Process via Sampling of Signals |
| title_short | Further Discussion on Modeling of Measuring Process via Sampling of Signals |
| title_sort | further discussion on modeling of measuring process via sampling of signals |
| topic | measuring process sampling of signals smearing and averaging of signal samples |
| url | https://journals.pan.pl/Content/117101/PDF/70_2407_Borys_skl_new.pdf |
| work_keys_str_mv | AT andrzejborys furtherdiscussiononmodelingofmeasuringprocessviasamplingofsignals |