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Real time identification of local su...

ProQuest Information and Learning Co.

Real time identification of local surface properties of material using atomic force microscope - An FPGA based implementation.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Real time identification of local surface properties of material using atomic force microscope - An FPGA based implementation./
作者:	Pradhan, Sourav.
面頁冊數:	1 online resource (66 pages)
附註:	Source: Masters Abstracts International, Volume: 56-03.
標題:	Electrical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369680218

Real time identification of local surface properties of material using atomic force microscope - An FPGA based implementation.
Pradhan, Sourav.

Real time identification of local surface properties of material using atomic force microscope - An FPGA based implementation. - 1 online resource (66 pages)

Source: Masters Abstracts International, Volume: 56-03.

Thesis (M.S.E.E.)--University of Minnesota, 2017.

Includes bibliographical references

System identification is widely employed for building mathematical models of manifold systems using statistical techniques. In this thesis, the application of system identification to atomic force microscopy using a real-time embedded solution has been reported. Atomic force microscopes are prevalent instruments utilized to explore material properties at the micro/nanometer level. A Field Programmable Gate Array has been chosen to harbor the design of the system identification module. The reported module has been successfully cascaded with an atomic force microscope to estimate local surface mechanical properties of materials. The design layout described in this thesis is not just applicable to commercially available atomic force microscopes, but to a large group of real-time signal processing units. Numerous simulations over multiple platforms and experimental results are presented to validate the accuracy and performance of the designed system identification module.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369680218Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Real time identification of local surface properties of material using atomic force microscope - An FPGA based implementation.
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245 1 0 $a Real time identification of local surface properties of material using atomic force microscope - An FPGA based implementation.
264 0 $c 2017
300 $a 1 online resource (66 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 56-03.
500 $a Adviser: Murti V. Salapaka.
502 $a Thesis (M.S.E.E.)--University of Minnesota, 2017.
504 $a Includes bibliographical references
520 $a System identification is widely employed for building mathematical models of manifold systems using statistical techniques. In this thesis, the application of system identification to atomic force microscopy using a real-time embedded solution has been reported. Atomic force microscopes are prevalent instruments utilized to explore material properties at the micro/nanometer level. A Field Programmable Gate Array has been chosen to harbor the design of the system identification module. The reported module has been successfully cascaded with an atomic force microscope to estimate local surface mechanical properties of materials. The design layout described in this thesis is not just applicable to commercially available atomic force microscopes, but to a large group of real-time signal processing units. Numerous simulations over multiple platforms and experimental results are presented to validate the accuracy and performance of the designed system identification module.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Minnesota. $b Electrical Engineering. $3 1148492
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10258605 $z click for full text (PQDT)

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