Finding the Probability Distribution Functions of S -Parameters and Their Monte Carlo Simulation
This paper presents the probability distribution function (PDF) of the ratio of two random waves. This result is used to obtain the PDF of S -parameters random errors in magnitude (in decibels) and phase, which are the quantities that most engineers work with. These results are further used on the d...
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| Veröffentlicht in: | IEEE transactions on instrumentation and measurement 2012-11, Vol.61 (11), p.2993-3002 |
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| container_title | IEEE transactions on instrumentation and measurement |
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| creator | Agili, Sedig S. Morales, A. W. Li, J. Resso, M. |
| description | This paper presents the probability distribution function (PDF) of the ratio of two random waves. This result is used to obtain the PDF of S -parameters random errors in magnitude (in decibels) and phase, which are the quantities that most engineers work with. These results are further used on the development of a Monte Carlo simulation method in order to predict the variability of frequency-domain measurements. Experiments are performed to identify and characterize frequency-domain random errors, such as instrument noise, connector repeatability, and calibration variations, in measurement systems. By comparing with real measurement data, it is shown that random-error effects can be accurately estimated by the PDF's obtained and the Monte Carlo technique. |
| doi_str_mv | 10.1109/TIM.2012.2202165 |
| format | Article |
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By comparing with real measurement data, it is shown that random-error effects can be accurately estimated by the PDF's obtained and the Monte Carlo technique.</description><subject>Calibration</subject><subject>Frequency measurement</subject><subject>Frequency-domain measurements</subject><subject>Measurement uncertainty</subject><subject>Monte Carlo method</subject><subject>Monte Carlo methods</subject><subject>Probability distribution</subject><subject>probability distribution function (PDF)</subject><subject>random errors</subject><subject>Random variables</subject><subject>Uncertainty</subject><subject>vector network analyzer (VNA)</subject><issn>0018-9456</issn><issn>1557-9662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMFKw0AQhhdRsFbvgpd9gdSZ2ewmPUq1tdBiofUcN8muXUkT2d0e-vYmtHiagZnv_-Fj7BFhggjT591yPSFAmhABoZJXbIRSZslUKbpmIwDMk2kq1S27C-EHADKVZiP2NXdt7dpvHveGb3xX6tI1Lp74qwvRu_IYXdfy-bGthiXwzvItTzba64OJxgeu25rv9sZ5vu7aaPhM-6bjW3c4NnpA7tmN1U0wD5c5Zp_zt93sPVl9LJazl1VSkRIxwdJKEDKTSkmsrc2RUlMZmapMKARNpGwu6qo_VNqS0KiVqHMQSNamJYkxg3Nu5bsQvLHFr3cH7U8FQjEYKnpDxWCouBjqkacz4owx_--K-k6Q4g_812JF</recordid><startdate>20121101</startdate><enddate>20121101</enddate><creator>Agili, Sedig S.</creator><creator>Morales, A. 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W.</creatorcontrib><creatorcontrib>Li, J.</creatorcontrib><creatorcontrib>Resso, M.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>IEEE transactions on instrumentation and measurement</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Agili, Sedig S.</au><au>Morales, A. W.</au><au>Li, J.</au><au>Resso, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Finding the Probability Distribution Functions of S -Parameters and Their Monte Carlo Simulation</atitle><jtitle>IEEE transactions on instrumentation and measurement</jtitle><stitle>TIM</stitle><date>2012-11-01</date><risdate>2012</risdate><volume>61</volume><issue>11</issue><spage>2993</spage><epage>3002</epage><pages>2993-3002</pages><issn>0018-9456</issn><eissn>1557-9662</eissn><coden>IEIMAO</coden><abstract>This paper presents the probability distribution function (PDF) of the ratio of two random waves. This result is used to obtain the PDF of S -parameters random errors in magnitude (in decibels) and phase, which are the quantities that most engineers work with. These results are further used on the development of a Monte Carlo simulation method in order to predict the variability of frequency-domain measurements. Experiments are performed to identify and characterize frequency-domain random errors, such as instrument noise, connector repeatability, and calibration variations, in measurement systems. By comparing with real measurement data, it is shown that random-error effects can be accurately estimated by the PDF's obtained and the Monte Carlo technique.</abstract><pub>IEEE</pub><doi>10.1109/TIM.2012.2202165</doi><tpages>10</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Calibration Frequency measurement Frequency-domain measurements Measurement uncertainty Monte Carlo method Monte Carlo methods Probability distribution probability distribution function (PDF) random errors Random variables Uncertainty vector network analyzer (VNA) |
| title | Finding the Probability Distribution Functions of S -Parameters and Their Monte Carlo Simulation |
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